Hugging Face's logo

ArneBinder
/
sam-pointer-bart-base-v0.3

Transformers
PyTorch
English
SimpleGenerativeModel
Inference Endpoints
Model card Files Community
1
sam-pointer-bart-base-v0.3 / output.log
ArneBinder's picture
ArneBinder
update model (#1)
76300f8 verified
raw
history blame
111 kB
[2024-05-28 23:33:58,508][__main__][INFO] - Save taskmodule to /home/arne/projects/pie-document-level/models/dataset-sciarg/task-ner_re/v0.3/2024-05-28_23-33-46 [push_to_hub=False]
[2024-05-28 23:33:58,512][__main__][INFO] - Starting training!
[2024-05-28 23:33:59,216][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A02 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=23576, end=23668, label='own_claim', score=1.0), tail=LabeledSpan(start=24841, end=25014, label='own_claim', score=1.0), label='semantically_same', score=1.0)}"
}
[2024-05-28 23:33:59,348][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A06 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=38474, end=38482, label='own_claim', score=1.0), tail=LabeledSpan(start=39445, end=39547, label='own_claim', score=1.0), label='parts_of_same', score=1.0)}"
}
[2024-05-28 23:33:59,567][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A13 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=36143, end=36172, label='own_claim', score=1.0), tail=LabeledSpan(start=37284, end=37312, label='own_claim', score=1.0), label='parts_of_same', score=1.0)}"
}
encode inputs: 37%|█████████████████████████████████████████████████▋ | 10/27 [00:01<00:02, 7.38it/s]
[2024-05-28 23:34:00,685][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A22 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=34492, end=34542, label='background_claim', score=1.0), tail=LabeledSpan(start=33705, end=33750, label='background_claim', score=1.0), label='supports', score=1.0)}"
}
[2024-05-28 23:34:01,674][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A01 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=9590, end=9619, label='own_claim', score=1.0), tail=LabeledSpan(start=15220, end=15338, label='own_claim', score=1.0), label='semantically_same', score=1.0), BinaryRelation(head=LabeledSpan(start=15220, end=15338, label='own_claim', score=1.0), tail=LabeledSpan(start=15478, end=15498, label='own_claim', score=1.0), label='semantically_same', score=1.0), BinaryRelation(head=LabeledSpan(start=17950, end=17980, label='own_claim', score=1.0), tail=LabeledSpan(start=28960, end=29042, label='own_claim', score=1.0), label='semantically_same', score=1.0), BinaryRelation(head=LabeledSpan(start=5866, end=5919, label='own_claim', score=1.0), tail=LabeledSpan(start=9263, end=9308, label='own_claim', score=1.0), label='semantically_same', score=1.0)}"
}
[2024-05-28 23:34:01,906][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A20 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=10323, end=10462, label='own_claim', score=1.0), tail=LabeledSpan(start=11788, end=11920, label='own_claim', score=1.0), label='semantically_same', score=1.0)}"
}
[2024-05-28 23:34:02,269][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A29 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=19620, end=19626, label='data', score=1.0), tail=LabeledSpan(start=19919, end=19964, label='own_claim', score=1.0), label='supports', score=1.0)}"
encode inputs: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 27/27 [00:03<00:00, 7.83it/s]
encode targets: 0%| | 0/537 [00:00<?, ?it/s]
encode targets: 82%|███████████████████████████████████████████████████████████████████████████████████████████████████████████ | 442/537 [00:02<00:00, 238.39it/s]
[2024-05-28 23:34:04,875][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A04 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=3205, end=3270, label='background_claim', score=1.0), tail=LabeledSpan(start=7724, end=7814, label='background_claim', score=1.0), label='semantically_same', score=1.0)}"
}
┏━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓
┃ ┃ Name ┃ Type ┃ Params ┃
┡━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩
│ 0 │ metric_val │ WrappedLayerMetricsWithUnbatchAndDecodeWithErrorsFunction │ 0 │
│ 1 │ metric_val.layer_metrics │ ModuleDict │ 0 │
│ 2 │ metric_val.layer_metrics.labeled_spans │ PrecisionRecallAndF1ForLabeledAnnotations │ 0 │
│ 3 │ metric_val.layer_metrics.binary_relations │ PrecisionRecallAndF1ForLabeledAnnotations │ 0 │
│ 4 │ metric_test │ WrappedLayerMetricsWithUnbatchAndDecodeWithErrorsFunction │ 0 │
│ 5 │ metric_test.layer_metrics │ ModuleDict │ 0 │
│ 6 │ metric_test.layer_metrics.labeled_spans │ PrecisionRecallAndF1ForLabeledAnnotations │ 0 │
│ 7 │ metric_test.layer_metrics.binary_relations │ PrecisionRecallAndF1ForLabeledAnnotations │ 0 │
│ 8 │ metric_train │ WrappedLayerMetricsWithUnbatchAndDecodeWithErrorsFunction │ 0 │
│ 9 │ metric_train.layer_metrics │ ModuleDict │ 0 │
│ 10 │ metric_train.layer_metrics.labeled_spans │ PrecisionRecallAndF1ForLabeledAnnotations │ 0 │
│ 11 │ metric_train.layer_metrics.binary_relations │ PrecisionRecallAndF1ForLabeledAnnotations │ 0 │
│ 12 │ model │ BartAsPointerNetwork │ 141 M │
│ 13 │ model.model │ BartModelWithDecoderPositionIds │ 139 M │
│ 14 │ model.model.shared │ Embedding │ 38.6 M │
│ 15 │ model.model.encoder │ BartEncoder │ 81.9 M │
│ 16 │ model.model.encoder.embed_positions │ BartLearnedPositionalEmbedding │ 787 K │
│ 17 │ model.model.encoder.layers │ ModuleList │ 42.5 M │
│ 18 │ model.model.encoder.layers.0 │ BartEncoderLayer │ 7.1 M │
│ 19 │ model.model.encoder.layers.0.self_attn │ BartSdpaAttention │ 2.4 M │
│ 20 │ model.model.encoder.layers.0.self_attn.k_proj │ Linear │ 590 K │
│ 21 │ model.model.encoder.layers.0.self_attn.v_proj │ Linear │ 590 K │
│ 22 │ model.model.encoder.layers.0.self_attn.q_proj │ Linear │ 590 K │
│ 23 │ model.model.encoder.layers.0.self_attn.out_proj │ Linear │ 590 K │
│ 24 │ model.model.encoder.layers.0.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 25 │ model.model.encoder.layers.0.activation_fn │ GELUActivation │ 0 │
│ 26 │ model.model.encoder.layers.0.fc1 │ Linear │ 2.4 M │
│ 27 │ model.model.encoder.layers.0.fc2 │ Linear │ 2.4 M │
│ 28 │ model.model.encoder.layers.0.final_layer_norm │ LayerNorm │ 1.5 K │
│ 29 │ model.model.encoder.layers.1 │ BartEncoderLayer │ 7.1 M │
│ 30 │ model.model.encoder.layers.1.self_attn │ BartSdpaAttention │ 2.4 M │
│ 31 │ model.model.encoder.layers.1.self_attn.k_proj │ Linear │ 590 K │
│ 32 │ model.model.encoder.layers.1.self_attn.v_proj │ Linear │ 590 K │
│ 33 │ model.model.encoder.layers.1.self_attn.q_proj │ Linear │ 590 K │
│ 34 │ model.model.encoder.layers.1.self_attn.out_proj │ Linear │ 590 K │
│ 35 │ model.model.encoder.layers.1.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 36 │ model.model.encoder.layers.1.activation_fn │ GELUActivation │ 0 │
│ 37 │ model.model.encoder.layers.1.fc1 │ Linear │ 2.4 M │
│ 38 │ model.model.encoder.layers.1.fc2 │ Linear │ 2.4 M │
│ 39 │ model.model.encoder.layers.1.final_layer_norm │ LayerNorm │ 1.5 K │
│ 40 │ model.model.encoder.layers.2 │ BartEncoderLayer │ 7.1 M │
│ 41 │ model.model.encoder.layers.2.self_attn │ BartSdpaAttention │ 2.4 M │
│ 42 │ model.model.encoder.layers.2.self_attn.k_proj │ Linear │ 590 K │
│ 43 │ model.model.encoder.layers.2.self_attn.v_proj │ Linear │ 590 K │
│ 44 │ model.model.encoder.layers.2.self_attn.q_proj │ Linear │ 590 K │
│ 45 │ model.model.encoder.layers.2.self_attn.out_proj │ Linear │ 590 K │
│ 46 │ model.model.encoder.layers.2.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 47 │ model.model.encoder.layers.2.activation_fn │ GELUActivation │ 0 │
│ 48 │ model.model.encoder.layers.2.fc1 │ Linear │ 2.4 M │
│ 49 │ model.model.encoder.layers.2.fc2 │ Linear │ 2.4 M │
│ 50 │ model.model.encoder.layers.2.final_layer_norm │ LayerNorm │ 1.5 K │
│ 51 │ model.model.encoder.layers.3 │ BartEncoderLayer │ 7.1 M │
│ 52 │ model.model.encoder.layers.3.self_attn │ BartSdpaAttention │ 2.4 M │
│ 53 │ model.model.encoder.layers.3.self_attn.k_proj │ Linear │ 590 K │
│ 54 │ model.model.encoder.layers.3.self_attn.v_proj │ Linear │ 590 K │
│ 55 │ model.model.encoder.layers.3.self_attn.q_proj │ Linear │ 590 K │
│ 56 │ model.model.encoder.layers.3.self_attn.out_proj │ Linear │ 590 K │
│ 57 │ model.model.encoder.layers.3.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 58 │ model.model.encoder.layers.3.activation_fn │ GELUActivation │ 0 │
│ 59 │ model.model.encoder.layers.3.fc1 │ Linear │ 2.4 M │
│ 60 │ model.model.encoder.layers.3.fc2 │ Linear │ 2.4 M │
│ 61 │ model.model.encoder.layers.3.final_layer_norm │ LayerNorm │ 1.5 K │
│ 62 │ model.model.encoder.layers.4 │ BartEncoderLayer │ 7.1 M │
│ 63 │ model.model.encoder.layers.4.self_attn │ BartSdpaAttention │ 2.4 M │
│ 64 │ model.model.encoder.layers.4.self_attn.k_proj │ Linear │ 590 K │
│ 65 │ model.model.encoder.layers.4.self_attn.v_proj │ Linear │ 590 K │
│ 66 │ model.model.encoder.layers.4.self_attn.q_proj │ Linear │ 590 K │
│ 67 │ model.model.encoder.layers.4.self_attn.out_proj │ Linear │ 590 K │
│ 68 │ model.model.encoder.layers.4.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 69 │ model.model.encoder.layers.4.activation_fn │ GELUActivation │ 0 │
│ 70 │ model.model.encoder.layers.4.fc1 │ Linear │ 2.4 M │
│ 71 │ model.model.encoder.layers.4.fc2 │ Linear │ 2.4 M │
│ 72 │ model.model.encoder.layers.4.final_layer_norm │ LayerNorm │ 1.5 K │
│ 73 │ model.model.encoder.layers.5 │ BartEncoderLayer │ 7.1 M │
│ 74 │ model.model.encoder.layers.5.self_attn │ BartSdpaAttention │ 2.4 M │
│ 75 │ model.model.encoder.layers.5.self_attn.k_proj │ Linear │ 590 K │
│ 76 │ model.model.encoder.layers.5.self_attn.v_proj │ Linear │ 590 K │
│ 77 │ model.model.encoder.layers.5.self_attn.q_proj │ Linear │ 590 K │
│ 78 │ model.model.encoder.layers.5.self_attn.out_proj │ Linear │ 590 K │
│ 79 │ model.model.encoder.layers.5.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 80 │ model.model.encoder.layers.5.activation_fn │ GELUActivation │ 0 │
│ 81 │ model.model.encoder.layers.5.fc1 │ Linear │ 2.4 M │
│ 82 │ model.model.encoder.layers.5.fc2 │ Linear │ 2.4 M │
│ 83 │ model.model.encoder.layers.5.final_layer_norm │ LayerNorm │ 1.5 K │
│ 84 │ model.model.encoder.layernorm_embedding │ LayerNorm │ 1.5 K │
│ 85 │ model.model.decoder │ BartDecoderWithPositionIds │ 96.1 M │
│ 86 │ model.model.decoder.embed_positions │ BartLearnedPositionalEmbeddingWithPositionIds │ 787 K │
│ 87 │ model.model.decoder.layers │ ModuleList │ 56.7 M │
│ 88 │ model.model.decoder.layers.0 │ BartDecoderLayer │ 9.5 M │
│ 89 │ model.model.decoder.layers.0.self_attn │ BartSdpaAttention │ 2.4 M │
│ 90 │ model.model.decoder.layers.0.self_attn.k_proj │ Linear │ 590 K │
│ 91 │ model.model.decoder.layers.0.self_attn.v_proj │ Linear │ 590 K │
│ 92 │ model.model.decoder.layers.0.self_attn.q_proj │ Linear │ 590 K │
│ 93 │ model.model.decoder.layers.0.self_attn.out_proj │ Linear │ 590 K │
│ 94 │ model.model.decoder.layers.0.activation_fn │ GELUActivation │ 0 │
│ 95 │ model.model.decoder.layers.0.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 96 │ model.model.decoder.layers.0.encoder_attn │ BartSdpaAttention │ 2.4 M │
│ 97 │ model.model.decoder.layers.0.encoder_attn.k_proj │ Linear │ 590 K │
│ 98 │ model.model.decoder.layers.0.encoder_attn.v_proj │ Linear │ 590 K │
│ 99 │ model.model.decoder.layers.0.encoder_attn.q_proj │ Linear │ 590 K │
│ 100 │ model.model.decoder.layers.0.encoder_attn.out_proj │ Linear │ 590 K │
│ 101 │ model.model.decoder.layers.0.encoder_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 102 │ model.model.decoder.layers.0.fc1 │ Linear │ 2.4 M │
│ 103 │ model.model.decoder.layers.0.fc2 │ Linear │ 2.4 M │
│ 104 │ model.model.decoder.layers.0.final_layer_norm │ LayerNorm │ 1.5 K │
│ 105 │ model.model.decoder.layers.1 │ BartDecoderLayer │ 9.5 M │
│ 106 │ model.model.decoder.layers.1.self_attn │ BartSdpaAttention │ 2.4 M │
│ 107 │ model.model.decoder.layers.1.self_attn.k_proj │ Linear │ 590 K │
│ 108 │ model.model.decoder.layers.1.self_attn.v_proj │ Linear │ 590 K │
│ 109 │ model.model.decoder.layers.1.self_attn.q_proj │ Linear │ 590 K │
│ 110 │ model.model.decoder.layers.1.self_attn.out_proj │ Linear │ 590 K │
│ 111 │ model.model.decoder.layers.1.activation_fn │ GELUActivation │ 0 │
│ 112 │ model.model.decoder.layers.1.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 113 │ model.model.decoder.layers.1.encoder_attn │ BartSdpaAttention │ 2.4 M │
│ 114 │ model.model.decoder.layers.1.encoder_attn.k_proj │ Linear │ 590 K │
│ 115 │ model.model.decoder.layers.1.encoder_attn.v_proj │ Linear │ 590 K │
│ 116 │ model.model.decoder.layers.1.encoder_attn.q_proj │ Linear │ 590 K │
│ 117 │ model.model.decoder.layers.1.encoder_attn.out_proj │ Linear │ 590 K │
│ 118 │ model.model.decoder.layers.1.encoder_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 119 │ model.model.decoder.layers.1.fc1 │ Linear │ 2.4 M │
│ 120 │ model.model.decoder.layers.1.fc2 │ Linear │ 2.4 M │
│ 121 │ model.model.decoder.layers.1.final_layer_norm │ LayerNorm │ 1.5 K │
│ 122 │ model.model.decoder.layers.2 │ BartDecoderLayer │ 9.5 M │
│ 123 │ model.model.decoder.layers.2.self_attn │ BartSdpaAttention │ 2.4 M │
│ 124 │ model.model.decoder.layers.2.self_attn.k_proj │ Linear │ 590 K │
│ 125 │ model.model.decoder.layers.2.self_attn.v_proj │ Linear │ 590 K │
│ 126 │ model.model.decoder.layers.2.self_attn.q_proj │ Linear │ 590 K │
│ 127 │ model.model.decoder.layers.2.self_attn.out_proj │ Linear │ 590 K │
│ 128 │ model.model.decoder.layers.2.activation_fn │ GELUActivation │ 0 │
│ 129 │ model.model.decoder.layers.2.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 130 │ model.model.decoder.layers.2.encoder_attn │ BartSdpaAttention │ 2.4 M │
│ 131 │ model.model.decoder.layers.2.encoder_attn.k_proj │ Linear │ 590 K │
│ 132 │ model.model.decoder.layers.2.encoder_attn.v_proj │ Linear │ 590 K │
│ 133 │ model.model.decoder.layers.2.encoder_attn.q_proj │ Linear │ 590 K │
│ 134 │ model.model.decoder.layers.2.encoder_attn.out_proj │ Linear │ 590 K │
│ 135 │ model.model.decoder.layers.2.encoder_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 136 │ model.model.decoder.layers.2.fc1 │ Linear │ 2.4 M │
│ 137 │ model.model.decoder.layers.2.fc2 │ Linear │ 2.4 M │
│ 138 │ model.model.decoder.layers.2.final_layer_norm │ LayerNorm │ 1.5 K │
│ 139 │ model.model.decoder.layers.3 │ BartDecoderLayer │ 9.5 M │
│ 140 │ model.model.decoder.layers.3.self_attn │ BartSdpaAttention │ 2.4 M │
│ 141 │ model.model.decoder.layers.3.self_attn.k_proj │ Linear │ 590 K │
│ 142 │ model.model.decoder.layers.3.self_attn.v_proj │ Linear │ 590 K │
│ 143 │ model.model.decoder.layers.3.self_attn.q_proj │ Linear │ 590 K │
│ 144 │ model.model.decoder.layers.3.self_attn.out_proj │ Linear │ 590 K │
│ 145 │ model.model.decoder.layers.3.activation_fn │ GELUActivation │ 0 │
│ 146 │ model.model.decoder.layers.3.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 147 │ model.model.decoder.layers.3.encoder_attn │ BartSdpaAttention │ 2.4 M │
│ 148 │ model.model.decoder.layers.3.encoder_attn.k_proj │ Linear │ 590 K │
│ 149 │ model.model.decoder.layers.3.encoder_attn.v_proj │ Linear │ 590 K │
│ 150 │ model.model.decoder.layers.3.encoder_attn.q_proj │ Linear │ 590 K │
│ 151 │ model.model.decoder.layers.3.encoder_attn.out_proj │ Linear │ 590 K │
│ 152 │ model.model.decoder.layers.3.encoder_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 153 │ model.model.decoder.layers.3.fc1 │ Linear │ 2.4 M │
│ 154 │ model.model.decoder.layers.3.fc2 │ Linear │ 2.4 M │
│ 155 │ model.model.decoder.layers.3.final_layer_norm │ LayerNorm │ 1.5 K │
│ 156 │ model.model.decoder.layers.4 │ BartDecoderLayer │ 9.5 M │
│ 157 │ model.model.decoder.layers.4.self_attn │ BartSdpaAttention │ 2.4 M │
│ 158 │ model.model.decoder.layers.4.self_attn.k_proj │ Linear │ 590 K │
│ 159 │ model.model.decoder.layers.4.self_attn.v_proj │ Linear │ 590 K │
│ 160 │ model.model.decoder.layers.4.self_attn.q_proj │ Linear │ 590 K │
│ 161 │ model.model.decoder.layers.4.self_attn.out_proj │ Linear │ 590 K │
│ 162 │ model.model.decoder.layers.4.activation_fn │ GELUActivation │ 0 │
│ 163 │ model.model.decoder.layers.4.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 164 │ model.model.decoder.layers.4.encoder_attn │ BartSdpaAttention │ 2.4 M │
│ 165 │ model.model.decoder.layers.4.encoder_attn.k_proj │ Linear │ 590 K │
│ 166 │ model.model.decoder.layers.4.encoder_attn.v_proj │ Linear │ 590 K │
│ 167 │ model.model.decoder.layers.4.encoder_attn.q_proj │ Linear │ 590 K │
│ 168 │ model.model.decoder.layers.4.encoder_attn.out_proj │ Linear │ 590 K │
│ 169 │ model.model.decoder.layers.4.encoder_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 170 │ model.model.decoder.layers.4.fc1 │ Linear │ 2.4 M │
│ 171 │ model.model.decoder.layers.4.fc2 │ Linear │ 2.4 M │
│ 172 │ model.model.decoder.layers.4.final_layer_norm │ LayerNorm │ 1.5 K │
│ 173 │ model.model.decoder.layers.5 │ BartDecoderLayer │ 9.5 M │
│ 174 │ model.model.decoder.layers.5.self_attn │ BartSdpaAttention │ 2.4 M │
│ 175 │ model.model.decoder.layers.5.self_attn.k_proj │ Linear │ 590 K │
│ 176 │ model.model.decoder.layers.5.self_attn.v_proj │ Linear │ 590 K │
│ 177 │ model.model.decoder.layers.5.self_attn.q_proj │ Linear │ 590 K │
│ 178 │ model.model.decoder.layers.5.self_attn.out_proj │ Linear │ 590 K │
│ 179 │ model.model.decoder.layers.5.activation_fn │ GELUActivation │ 0 │
│ 180 │ model.model.decoder.layers.5.self_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 181 │ model.model.decoder.layers.5.encoder_attn │ BartSdpaAttention │ 2.4 M │
│ 182 │ model.model.decoder.layers.5.encoder_attn.k_proj │ Linear │ 590 K │
│ 183 │ model.model.decoder.layers.5.encoder_attn.v_proj │ Linear │ 590 K │
│ 184 │ model.model.decoder.layers.5.encoder_attn.q_proj │ Linear │ 590 K │
│ 185 │ model.model.decoder.layers.5.encoder_attn.out_proj │ Linear │ 590 K │
│ 186 │ model.model.decoder.layers.5.encoder_attn_layer_norm │ LayerNorm │ 1.5 K │
│ 187 │ model.model.decoder.layers.5.fc1 │ Linear │ 2.4 M │
│ 188 │ model.model.decoder.layers.5.fc2 │ Linear │ 2.4 M │
│ 189 │ model.model.decoder.layers.5.final_layer_norm │ LayerNorm │ 1.5 K │
│ 190 │ model.model.decoder.layernorm_embedding │ LayerNorm │ 1.5 K │
│ 191 │ model.pointer_head │ PointerHead │ 41.0 M │
│ 192 │ model.pointer_head.encoder_mlp │ Sequential │ 1.2 M │
│ 193 │ model.pointer_head.encoder_mlp.0 │ Linear │ 590 K │
│ 194 │ model.pointer_head.encoder_mlp.1 │ Dropout │ 0 │
│ 195 │ model.pointer_head.encoder_mlp.2 │ ReLU │ 0 │
│ 196 │ model.pointer_head.encoder_mlp.3 │ Linear │ 590 K │
│ 197 │ model.pointer_head.constraints_encoder_mlp │ Sequential │ 1.2 M │
│ 198 │ model.pointer_head.constraints_encoder_mlp.0 │ Linear │ 590 K │
│ 199 │ model.pointer_head.constraints_encoder_mlp.1 │ Dropout │ 0 │
│ 200 │ model.pointer_head.constraints_encoder_mlp.2 │ ReLU │ 0 │
│ 201 │ model.pointer_head.constraints_encoder_mlp.3 │ Linear │ 590 K │
└─────┴──────────────────────────────────────────────────────┴───────────────────────────────────────────────────────────┴────────┘
Trainable params: 141 M
Non-trainable params: 0
Total params: 141 M
Total estimated model params size (MB): 567
/home/arne/miniconda3/envs/pie-document-level/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'val_dataloader' does not have many workers
which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=11` in the `DataLoader` to improve performance.
/home/arne/miniconda3/envs/pie-document-level/lib/python3.9/site-packages/transformers/generation/utils.py:1197: UserWarning: You have modified the pretrained model configuration to
control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use and modify the model generation configuration (see
https://huggingface.co/docs/transformers/generation_strategies#default-text-generation-configuration )
encode targets: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 537/537 [00:02<00:00, 222.45it/s]
encode inputs: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 10.53it/s]
encode targets: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 72/72 [00:00<00:00, 231.24it/s]
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Loading `train_dataloader` to estimate number of stepping batches.
/home/arne/miniconda3/envs/pie-document-level/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'train_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=11` in the `DataLoader` to improve performance.
Epoch 0/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 5.348
Epoch 1/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.89it/s v_num: 91di loss/train_step: 4.651 loss/val: 5.071 loss/train_epoch: 5.349
Epoch 2/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.84it/s v_num: 91di loss/train_step: 5.185 loss/val: 3.677 loss/train_epoch: 4.854
Epoch 3/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.85it/s v_num: 91di loss/train_step: 3.813 loss/val: 3.471 loss/train_epoch: 4.415
Epoch 4/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.72it/s v_num: 91di loss/train_step: 2.717 loss/val: 2.595 loss/train_epoch: 4.252
Epoch 5/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 3.089 loss/val: 2.219 loss/train_epoch: 3.127
Epoch 6/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.72it/s v_num: 91di loss/train_step: 3.199 loss/val: 2.075 loss/train_epoch: 2.683
Epoch 7/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 2.419 loss/val: 1.917 loss/train_epoch: 2.521
Epoch 8/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.89it/s v_num: 91di loss/train_step: 2.774 loss/val: 1.801 loss/train_epoch: 2.188
Epoch 9/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 0.161 loss/val: 1.802 loss/train_epoch: 2.138
Epoch 10/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.95it/s v_num: 91di loss/train_step: 2.037 loss/val: 1.605 loss/train_epoch: 2.026
Epoch 11/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.88it/s v_num: 91di loss/train_step: 2.007 loss/val: 1.410 loss/train_epoch: 1.764
Epoch 12/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.76it/s v_num: 91di loss/train_step: 1.451 loss/val: 1.374 loss/train_epoch: 1.689
Epoch 13/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.92it/s v_num: 91di loss/train_step: 0.793 loss/val: 1.232 loss/train_epoch: 1.381
Epoch 14/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.78it/s v_num: 91di loss/train_step: 1.384 loss/val: 1.248 loss/train_epoch: 1.386
Epoch 15/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.90it/s v_num: 91di loss/train_step: 1.072 loss/val: 1.184 loss/train_epoch: 1.141
Epoch 16/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.98it/s v_num: 91di loss/train_step: 0.182 loss/val: 1.105 loss/train_epoch: 1.041
Epoch 17/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.78it/s v_num: 91di loss/train_step: 0.782 loss/val: 1.127 loss/train_epoch: 0.931
Epoch 18/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.84it/s v_num: 91di loss/train_step: 0.855 loss/val: 1.123 loss/train_epoch: 0.865
Epoch 19/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.64it/s v_num: 91di loss/train_step: 0.745 loss/val: 1.117 loss/train_epoch: 0.771
Epoch 20/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 6.08it/s v_num: 91di loss/train_step: 1.241 loss/val: 1.065 loss/train_epoch: 0.750
Epoch 21/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.81it/s v_num: 91di loss/train_step: 0.645 loss/val: 1.074 loss/train_epoch: 0.737
Epoch 22/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.75it/s v_num: 91di loss/train_step: 0.422 loss/val: 1.103 loss/train_epoch: 0.682
Epoch 23/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.78it/s v_num: 91di loss/train_step: 0.125 loss/val: 1.159 loss/train_epoch: 0.613
Epoch 24/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.679 loss/val: 1.104 loss/train_epoch: 0.603
Epoch 25/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.72it/s v_num: 91di loss/train_step: 0.399 loss/val: 1.202 loss/train_epoch: 0.538
Epoch 26/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.85it/s v_num: 91di loss/train_step: 0.559 loss/val: 1.146 loss/train_epoch: 0.538
Epoch 27/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.75it/s v_num: 91di loss/train_step: 0.696 loss/val: 1.154 loss/train_epoch: 0.492
Epoch 28/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.89it/s v_num: 91di loss/train_step: 0.314 loss/val: 1.223 loss/train_epoch: 0.452
Epoch 29/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.84it/s v_num: 91di loss/train_step: 0.831 loss/val: 1.245 loss/train_epoch: 0.417
Epoch 30/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.74it/s v_num: 91di loss/train_step: 0.603 loss/val: 1.228 loss/train_epoch: 0.441
Epoch 31/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.166 loss/val: 1.257 loss/train_epoch: 0.410
Epoch 32/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.77it/s v_num: 91di loss/train_step: 0.080 loss/val: 1.371 loss/train_epoch: 0.369
Epoch 33/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.90it/s v_num: 91di loss/train_step: 0.463 loss/val: 1.380 loss/train_epoch: 0.347
Epoch 34/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.98it/s v_num: 91di loss/train_step: 0.130 loss/val: 1.409 loss/train_epoch: 0.338
Epoch 35/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.98it/s v_num: 91di loss/train_step: 0.221 loss/val: 1.524 loss/train_epoch: 0.316
Epoch 36/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.90it/s v_num: 91di loss/train_step: 0.195 loss/val: 1.582 loss/train_epoch: 0.303
Epoch 37/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.85it/s v_num: 91di loss/train_step: 0.112 loss/val: 1.523 loss/train_epoch: 0.303
Epoch 38/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.86it/s v_num: 91di loss/train_step: 0.649 loss/val: 1.394 loss/train_epoch: 0.303
Epoch 39/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.77it/s v_num: 91di loss/train_step: 0.247 loss/val: 1.421 loss/train_epoch: 0.293
Epoch 40/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.74it/s v_num: 91di loss/train_step: 0.129 loss/val: 1.397 loss/train_epoch: 0.283
Epoch 41/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.89it/s v_num: 91di loss/train_step: 0.269 loss/val: 1.445 loss/train_epoch: 0.247
Epoch 42/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.187 loss/val: 1.516 loss/train_epoch: 0.245
Epoch 43/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.94it/s v_num: 91di loss/train_step: 0.422 loss/val: 1.480 loss/train_epoch: 0.238
Epoch 44/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.91it/s v_num: 91di loss/train_step: 0.315 loss/val: 1.524 loss/train_epoch: 0.227
Epoch 45/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.94it/s v_num: 91di loss/train_step: 0.203 loss/val: 1.493 loss/train_epoch: 0.223
Epoch 46/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.097 loss/val: 1.513 loss/train_epoch: 0.228
Epoch 47/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.202 loss/val: 1.626 loss/train_epoch: 0.215
Epoch 48/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.86it/s v_num: 91di loss/train_step: 0.198 loss/val: 1.830 loss/train_epoch: 0.196
Epoch 49/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.72it/s v_num: 91di loss/train_step: 0.238 loss/val: 1.544 loss/train_epoch: 0.193
Epoch 50/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.71it/s v_num: 91di loss/train_step: 0.188 loss/val: 1.625 loss/train_epoch: 0.183
Epoch 51/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.89it/s v_num: 91di loss/train_step: 0.089 loss/val: 1.623 loss/train_epoch: 0.197
Epoch 52/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 0.090 loss/val: 1.546 loss/train_epoch: 0.212
Epoch 53/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.78it/s v_num: 91di loss/train_step: 0.216 loss/val: 1.505 loss/train_epoch: 0.199
Epoch 54/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.85it/s v_num: 91di loss/train_step: 0.201 loss/val: 1.678 loss/train_epoch: 0.162
Epoch 55/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.90it/s v_num: 91di loss/train_step: 0.064 loss/val: 1.652 loss/train_epoch: 0.154
Epoch 56/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.91it/s v_num: 91di loss/train_step: 0.041 loss/val: 1.553 loss/train_epoch: 0.157
Epoch 57/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.86it/s v_num: 91di loss/train_step: 0.217 loss/val: 1.675 loss/train_epoch: 0.148
Epoch 58/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.75it/s v_num: 91di loss/train_step: 0.113 loss/val: 1.723 loss/train_epoch: 0.139
Epoch 59/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.77it/s v_num: 91di loss/train_step: 0.104 loss/val: 1.795 loss/train_epoch: 0.136
Epoch 60/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.91it/s v_num: 91di loss/train_step: 0.069 loss/val: 1.769 loss/train_epoch: 0.133
Epoch 61/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 6.06it/s v_num: 91di loss/train_step: 0.127 loss/val: 1.640 loss/train_epoch: 0.133
Epoch 62/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 0.246 loss/val: 1.746 loss/train_epoch: 0.146
Epoch 63/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.629 loss/val: 1.645 loss/train_epoch: 0.148
Epoch 64/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.80it/s v_num: 91di loss/train_step: 0.111 loss/val: 1.741 loss/train_epoch: 0.131
Epoch 65/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.233 loss/val: 1.862 loss/train_epoch: 0.121
Epoch 66/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.96it/s v_num: 91di loss/train_step: 0.073 loss/val: 1.758 loss/train_epoch: 0.145
Epoch 67/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.99it/s v_num: 91di loss/train_step: 0.028 loss/val: 1.794 loss/train_epoch: 0.137
Epoch 68/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.83it/s v_num: 91di loss/train_step: 0.026 loss/val: 1.717 loss/train_epoch: 0.132
Epoch 69/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.86it/s v_num: 91di loss/train_step: 0.123 loss/val: 1.874 loss/train_epoch: 0.113
Epoch 70/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.80it/s v_num: 91di loss/train_step: 0.045 loss/val: 1.794 loss/train_epoch: 0.124
Epoch 71/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.100 loss/val: 1.785 loss/train_epoch: 0.119
Epoch 72/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.91it/s v_num: 91di loss/train_step: 0.034 loss/val: 1.798 loss/train_epoch: 0.107
Epoch 73/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.105 loss/val: 1.776 loss/train_epoch: 0.105
Epoch 74/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.93it/s v_num: 91di loss/train_step: 0.168 loss/val: 1.799 loss/train_epoch: 0.129
Epoch 75/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.065 loss/val: 1.889 loss/train_epoch: 0.105
Epoch 76/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.035 loss/val: 1.877 loss/train_epoch: 0.109
Epoch 77/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.83it/s v_num: 91di loss/train_step: 0.078 loss/val: 1.928 loss/train_epoch: 0.097
Epoch 78/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.88it/s v_num: 91di loss/train_step: 0.131 loss/val: 1.931 loss/train_epoch: 0.109
Epoch 79/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.70it/s v_num: 91di loss/train_step: 0.099 loss/val: 1.792 loss/train_epoch: 0.114
Epoch 80/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.74it/s v_num: 91di loss/train_step: 0.059 loss/val: 1.861 loss/train_epoch: 0.114
Epoch 81/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.85it/s v_num: 91di loss/train_step: 0.023 loss/val: 1.913 loss/train_epoch: 0.104
Epoch 82/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.044 loss/val: 1.905 loss/train_epoch: 0.089
Epoch 83/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.74it/s v_num: 91di loss/train_step: 0.072 loss/val: 1.943 loss/train_epoch: 0.091
Epoch 84/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.78it/s v_num: 91di loss/train_step: 0.083 loss/val: 1.943 loss/train_epoch: 0.089
Epoch 85/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.80it/s v_num: 91di loss/train_step: 0.039 loss/val: 1.942 loss/train_epoch: 0.100
Epoch 86/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.83it/s v_num: 91di loss/train_step: 0.040 loss/val: 1.911 loss/train_epoch: 0.080
Epoch 87/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.76it/s v_num: 91di loss/train_step: 0.056 loss/val: 1.917 loss/train_epoch: 0.088
Epoch 88/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.85it/s v_num: 91di loss/train_step: 0.113 loss/val: 1.911 loss/train_epoch: 0.084
Epoch 89/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.81it/s v_num: 91di loss/train_step: 0.035 loss/val: 1.832 loss/train_epoch: 0.096
Epoch 90/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.96it/s v_num: 91di loss/train_step: 0.200 loss/val: 1.940 loss/train_epoch: 0.078
Epoch 91/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.84it/s v_num: 91di loss/train_step: 0.037 loss/val: 1.810 loss/train_epoch: 0.152
Epoch 92/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.86it/s v_num: 91di loss/train_step: 0.061 loss/val: 1.882 loss/train_epoch: 0.097
Epoch 93/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.86it/s v_num: 91di loss/train_step: 0.032 loss/val: 1.924 loss/train_epoch: 0.086
Epoch 94/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.78it/s v_num: 91di loss/train_step: 0.065 loss/val: 1.964 loss/train_epoch: 0.088
Epoch 95/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 0.175 loss/val: 2.014 loss/train_epoch: 0.072
Epoch 96/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.098 loss/val: 2.006 loss/train_epoch: 0.082
Epoch 97/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.83it/s v_num: 91di loss/train_step: 0.039 loss/val: 2.039 loss/train_epoch: 0.073
Epoch 98/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.75it/s v_num: 91di loss/train_step: 0.183 loss/val: 2.132 loss/train_epoch: 0.087
Epoch 99/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.86it/s v_num: 91di loss/train_step: 0.369 loss/val: 2.105 loss/train_epoch: 0.076
Epoch 100/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.70it/s v_num: 91di loss/train_step: 0.041 loss/val: 2.049 loss/train_epoch: 0.076
Epoch 101/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.94it/s v_num: 91di loss/train_step: 0.036 loss/val: 2.143 loss/train_epoch: 0.077
Epoch 102/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.77it/s v_num: 91di loss/train_step: 0.081 loss/val: 2.091 loss/train_epoch: 0.075
Epoch 103/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.75it/s v_num: 91di loss/train_step: 0.033 loss/val: 2.147 loss/train_epoch: 0.076
Epoch 104/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.88it/s v_num: 91di loss/train_step: 0.132 loss/val: 2.083 loss/train_epoch: 0.081
Epoch 105/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.73it/s v_num: 91di loss/train_step: 0.021 loss/val: 2.136 loss/train_epoch: 0.079
Epoch 106/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.77it/s v_num: 91di loss/train_step: 0.175 loss/val: 2.173 loss/train_epoch: 0.068
Epoch 107/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.96it/s v_num: 91di loss/train_step: 0.032 loss/val: 2.089 loss/train_epoch: 0.075
Epoch 108/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.84it/s v_num: 91di loss/train_step: 0.038 loss/val: 2.221 loss/train_epoch: 0.071
Epoch 109/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.046 loss/val: 2.048 loss/train_epoch: 0.077
Epoch 110/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.78it/s v_num: 91di loss/train_step: 0.033 loss/val: 2.112 loss/train_epoch: 0.069
Epoch 111/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.84it/s v_num: 91di loss/train_step: 0.043 loss/val: 2.121 loss/train_epoch: 0.068
Epoch 112/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.63it/s v_num: 91di loss/train_step: 0.033 loss/val: 2.148 loss/train_epoch: 0.072
Epoch 113/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.80it/s v_num: 91di loss/train_step: 0.035 loss/val: 2.160 loss/train_epoch: 0.068
Epoch 114/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.88it/s v_num: 91di loss/train_step: 0.047 loss/val: 2.233 loss/train_epoch: 0.075
Epoch 115/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.89it/s v_num: 91di loss/train_step: 0.056 loss/val: 2.143 loss/train_epoch: 0.066
Epoch 116/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.77it/s v_num: 91di loss/train_step: 0.047 loss/val: 2.137 loss/train_epoch: 0.064
Epoch 117/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.065 loss/val: 2.219 loss/train_epoch: 0.061
Epoch 118/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.99it/s v_num: 91di loss/train_step: 0.022 loss/val: 2.201 loss/train_epoch: 0.072
Epoch 119/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.68it/s v_num: 91di loss/train_step: 0.023 loss/val: 2.236 loss/train_epoch: 0.070
Epoch 120/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.71it/s v_num: 91di loss/train_step: 0.030 loss/val: 2.254 loss/train_epoch: 0.066
Epoch 121/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.052 loss/val: 2.163 loss/train_epoch: 0.071
Epoch 122/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.70it/s v_num: 91di loss/train_step: 0.055 loss/val: 2.212 loss/train_epoch: 0.075
Epoch 123/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 0.026 loss/val: 2.267 loss/train_epoch: 0.067
Epoch 124/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.92it/s v_num: 91di loss/train_step: 0.020 loss/val: 2.247 loss/train_epoch: 0.071
Epoch 125/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.91it/s v_num: 91di loss/train_step: 0.072 loss/val: 2.169 loss/train_epoch: 0.070
Epoch 126/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.83it/s v_num: 91di loss/train_step: 0.685 loss/val: 2.217 loss/train_epoch: 0.063
Epoch 127/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.046 loss/val: 2.225 loss/train_epoch: 0.065
Epoch 128/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.89it/s v_num: 91di loss/train_step: 0.021 loss/val: 2.262 loss/train_epoch: 0.059
Epoch 129/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.87it/s v_num: 91di loss/train_step: 0.030 loss/val: 2.257 loss/train_epoch: 0.060
Epoch 130/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.74it/s v_num: 91di loss/train_step: 0.038 loss/val: 2.274 loss/train_epoch: 0.059
Epoch 131/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.91it/s v_num: 91di loss/train_step: 0.030 loss/val: 2.288 loss/train_epoch: 0.059
Epoch 132/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.413 loss/val: 2.227 loss/train_epoch: 0.064
Epoch 133/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.023 loss/val: 2.291 loss/train_epoch: 0.061
Epoch 134/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.76it/s v_num: 91di loss/train_step: 0.038 loss/val: 2.346 loss/train_epoch: 0.058
Epoch 135/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.98it/s v_num: 91di loss/train_step: 0.040 loss/val: 2.342 loss/train_epoch: 0.056
Epoch 136/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.83it/s v_num: 91di loss/train_step: 0.024 loss/val: 2.382 loss/train_epoch: 0.055
Epoch 137/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.88it/s v_num: 91di loss/train_step: 0.060 loss/val: 2.370 loss/train_epoch: 0.060
Epoch 138/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.80it/s v_num: 91di loss/train_step: 0.029 loss/val: 2.350 loss/train_epoch: 0.060
Epoch 139/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.97it/s v_num: 91di loss/train_step: 0.020 loss/val: 2.357 loss/train_epoch: 0.061
Epoch 140/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.91it/s v_num: 91di loss/train_step: 0.018 loss/val: 2.340 loss/train_epoch: 0.074
Epoch 141/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.82it/s v_num: 91di loss/train_step: 0.038 loss/val: 2.392 loss/train_epoch: 0.056
Epoch 142/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.92it/s v_num: 91di loss/train_step: 0.023 loss/val: 2.362 loss/train_epoch: 0.062
Epoch 143/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.98it/s v_num: 91di loss/train_step: 0.057 loss/val: 2.396 loss/train_epoch: 0.068
Epoch 144/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.72it/s v_num: 91di loss/train_step: 0.053 loss/val: 2.407 loss/train_epoch: 0.064
Epoch 145/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.83it/s v_num: 91di loss/train_step: 0.181 loss/val: 2.387 loss/train_epoch: 0.061
Epoch 146/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.031 loss/val: 2.404 loss/train_epoch: 0.065
Epoch 147/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.79it/s v_num: 91di loss/train_step: 0.028 loss/val: 2.356 loss/train_epoch: 0.052
Epoch 148/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:46 • 0:00:00 5.85it/s v_num: 91di loss/train_step: 0.030 loss/val: 2.376 loss/train_epoch: 0.058
Epoch 149/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.72it/s v_num: 91di loss/train_step: 0.028 loss/val: 2.393 loss/train_epoch: 0.051
Validation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━━━ 33/36  0:00:59 • 0:00:06 0.58it/s
`Trainer.fit` stopped: `max_epochs=150` reached.
/home/arne/miniconda3/envs/pie-document-level/lib/python3.9/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
Epoch 149/149 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 268/268 0:00:45 • 0:00:00 5.72it/s v_num: 91di loss/train_step: 0.028 loss/val: 2.378 loss/train_epoch: 0.059
[?25h[2024-05-29 04:19:31,092][__main__][INFO] - Best ckpt path: /mnt/data/experiments/pie-document-level/logs/training/multiruns/dataset-sciarg/task-ner_re/v0.3/2024-05-28_18-12-11/1/checkpoints/epoch_146.ckpt
Some weights of BartAsPointerNetwork were not initialized from the model checkpoint at facebook/bart-base and are newly initialized: ['pointer_head.constraints_encoder_mlp.0.bias', 'pointer_head.constraints_encoder_mlp.0.weight', 'pointer_head.constraints_encoder_mlp.3.bias', 'pointer_head.constraints_encoder_mlp.3.weight', 'pointer_head.decoder_position_id_pattern', 'pointer_head.encoder_mlp.0.bias', 'pointer_head.encoder_mlp.0.weight', 'pointer_head.encoder_mlp.3.bias', 'pointer_head.encoder_mlp.3.weight', 'pointer_head.target2token_id']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
encode inputs: 50%|████████████████████████████████████████████████████████████████████ | 2/4 [00:00<00:00, 10.79it/s]
[2024-05-29 04:19:34,073][__main__][INFO] - Save model to /home/arne/projects/pie-document-level/models/dataset-sciarg/task-ner_re/v0.3/2024-05-28_23-33-46 [push_to_hub=False]
[2024-05-29 04:19:34,508][__main__][INFO] - Starting validation!
[2024-05-29 04:19:34,626][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A04 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=3205, end=3270, label='background_claim', score=1.0), tail=LabeledSpan(start=7724, end=7814, label='background_claim', score=1.0), label='semantically_same', score=1.0)}"
encode inputs: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4/4 [00:00<00:00, 10.55it/s]
encode targets: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 72/72 [00:00<00:00, 238.68it/s]
Restoring states from the checkpoint path at /mnt/data/experiments/pie-document-level/logs/training/multiruns/dataset-sciarg/task-ner_re/v0.3/2024-05-28_18-12-11/1/checkpoints/epoch_146.ckpt
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Loaded model weights from the checkpoint at /mnt/data/experiments/pie-document-level/logs/training/multiruns/dataset-sciarg/task-ner_re/v0.3/2024-05-28_18-12-11/1/checkpoints/epoch_146.ckpt
Validation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━━━ 33/36 0:00:57 • 0:00:05 0.64it/s
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Validate metric ┃ DataLoader 0 ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ loss/val │ 2.3559770584106445 │
│ metric/binary_relations/contradicts/f1/val │ 0.20481927692890167 │
│ metric/binary_relations/contradicts/precision/val │ 0.2266666740179062 │
│ metric/binary_relations/contradicts/recall/val │ 0.18681319057941437 │
│ metric/binary_relations/macro/f1/val │ 0.16949915885925293 │
│ metric/binary_relations/macro/precision/val │ 0.1830090433359146 │
│ metric/binary_relations/macro/recall/val │ 0.15798917412757874 │
│ metric/binary_relations/micro/f1/val │ 0.23862887918949127 │
│ metric/binary_relations/micro/precision/val │ 0.25931233167648315 │
│ metric/binary_relations/micro/recall/val │ 0.22100122272968292 │
│ metric/binary_relations/parts_of_same/f1/val │ 0.22608695924282074 │
│ metric/binary_relations/parts_of_same/precision/val │ 0.23636363446712494 │
│ metric/binary_relations/parts_of_same/recall/val │ 0.21666666865348816 │
│ metric/binary_relations/semantically_same/f1/val │ 0.0 │
│ metric/binary_relations/semantically_same/precision/val │ 0.0 │
│ metric/binary_relations/semantically_same/recall/val │ 0.0 │
│ metric/binary_relations/supports/f1/val │ 0.2470904141664505 │
│ metric/binary_relations/supports/precision/val │ 0.26900583505630493 │
│ metric/binary_relations/supports/recall/val │ 0.22847682237625122 │
│ metric/decoding_errors/all/val │ 0.0 │
│ metric/decoding_errors/correct/val │ 1.0 │
│ metric/exact_encoding_matches/val │ 0.3611111044883728 │
│ metric/labeled_spans/background_claim/f1/val │ 0.5077399015426636 │
│ metric/labeled_spans/background_claim/precision/val │ 0.4984802305698395 │
│ metric/labeled_spans/background_claim/recall/val │ 0.5173501372337341 │
│ metric/labeled_spans/data/f1/val │ 0.536285400390625 │
│ metric/labeled_spans/data/precision/val │ 0.5797872543334961 │
│ metric/labeled_spans/data/recall/val │ 0.4988558292388916 │
│ metric/labeled_spans/macro/f1/val │ 0.49655672907829285 │
│ metric/labeled_spans/macro/precision/val │ 0.4986630082130432 │
│ metric/labeled_spans/macro/recall/val │ 0.49792489409446716 │
│ metric/labeled_spans/micro/f1/val │ 0.4843537509441376 │
│ metric/labeled_spans/micro/precision/val │ 0.4762541949748993 │
│ metric/labeled_spans/micro/recall/val │ 0.49273356795310974 │
│ metric/labeled_spans/own_claim/f1/val │ 0.4456448256969452 │
│ metric/labeled_spans/own_claim/precision/val │ 0.4177215099334717 │
│ metric/labeled_spans/own_claim/recall/val │ 0.47756874561309814 │
└─────────────────────────────────────────────────────────┴─────────────────────────────────────────────────────────┘
Validation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 36/36 0:01:00 • 0:00:00 0.64it/s
encode inputs: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 9/9 [00:01<00:00, 7.49it/s]
encode targets: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 165/165 [00:00<00:00, 257.10it/s]
Restoring states from the checkpoint path at /mnt/data/experiments/pie-document-level/logs/training/multiruns/dataset-sciarg/task-ner_re/v0.3/2024-05-28_18-12-11/1/checkpoints/epoch_146.ckpt
[2024-05-29 04:20:37,543][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A35 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=20713, end=20836, label='own_claim', score=1.0), tail=LabeledSpan(start=19655, end=19670, label='own_claim', score=1.0), label='contradicts', score=1.0)}"
}
[2024-05-29 04:20:38,104][pie_modules.document.processing.tokenization][WARNING] - could not convert all annotations from document with id=A40 to token based documents, missed annotations (disable this message with verbose=False):
{
"binary_relations": "{BinaryRelation(head=LabeledSpan(start=16497, end=16501, label='data', score=1.0), tail=LabeledSpan(start=17415, end=17613, label='background_claim', score=1.0), label='supports', score=1.0)}"
}
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Loaded model weights from the checkpoint at /mnt/data/experiments/pie-document-level/logs/training/multiruns/dataset-sciarg/task-ner_re/v0.3/2024-05-28_18-12-11/1/checkpoints/epoch_146.ckpt
/home/arne/miniconda3/envs/pie-document-level/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:441: The 'test_dataloader' does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` to `num_workers=11` in the `DataLoader` to improve performance.
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ Test metric ┃ DataLoader 0 ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ loss/test │ 3.026346206665039 │
│ metric/binary_relations/contradicts/f1/test │ 0.22545455396175385 │
│ metric/binary_relations/contradicts/precision/test │ 0.2246376872062683 │
│ metric/binary_relations/contradicts/recall/test │ 0.22627736628055573 │
│ metric/binary_relations/macro/f1/test │ 0.2669767737388611 │
│ metric/binary_relations/macro/precision/test │ 0.24492204189300537 │
│ metric/binary_relations/macro/recall/test │ 0.31745821237564087 │
│ metric/binary_relations/micro/f1/test │ 0.21676044166088104 │
│ metric/binary_relations/micro/precision/test │ 0.22932331264019012 │
│ metric/binary_relations/micro/recall/test │ 0.20550252497196198 │
│ metric/binary_relations/parts_of_same/f1/test │ 0.17359857261180878 │
│ metric/binary_relations/parts_of_same/precision/test │ 0.1818181872367859 │
│ metric/binary_relations/parts_of_same/recall/test │ 0.1660899668931961 │
│ metric/binary_relations/semantically_same/f1/test │ 0.444444477558136 │
│ metric/binary_relations/semantically_same/precision/test │ 0.3333333432674408 │
│ metric/binary_relations/semantically_same/recall/test │ 0.6666666865348816 │
│ metric/binary_relations/supports/f1/test │ 0.22440946102142334 │
│ metric/binary_relations/supports/precision/test │ 0.23989899456501007 │
│ metric/binary_relations/supports/recall/test │ 0.21079881489276886 │
│ metric/decoding_errors/all/test │ 0.20856545865535736 │
│ metric/decoding_errors/correct/test │ 0.7914345264434814 │
│ metric/decoding_errors/index/test │ 0.00034818940912373364 │
│ metric/decoding_errors/len/test │ 0.20821726322174072 │
│ metric/exact_encoding_matches/test │ 0.34545454382896423 │
│ metric/labeled_spans/background_claim/f1/test │ 0.42137405276298523 │
│ metric/labeled_spans/background_claim/precision/test │ 0.4502446949481964 │
│ metric/labeled_spans/background_claim/recall/test │ 0.3959827721118927 │
│ metric/labeled_spans/data/f1/test │ 0.5156335234642029 │
│ metric/labeled_spans/data/precision/test │ 0.5328798294067383 │
│ metric/labeled_spans/data/recall/test │ 0.4994686543941498 │
│ metric/labeled_spans/macro/f1/test │ 0.43463802337646484 │
│ metric/labeled_spans/macro/precision/test │ 0.4366190433502197 │
│ metric/labeled_spans/macro/recall/test │ 0.43793198466300964 │
│ metric/labeled_spans/micro/f1/test │ 0.42222580313682556 │
│ metric/labeled_spans/micro/precision/test │ 0.40691158175468445 │
│ metric/labeled_spans/micro/recall/test │ 0.4387378394603729 │
│ metric/labeled_spans/own_claim/f1/test │ 0.36690646409988403 │
│ metric/labeled_spans/own_claim/precision/test │ 0.32673266530036926 │
│ metric/labeled_spans/own_claim/recall/test │ 0.41834452748298645 │
└──────────────────────────────────────────────────────────┴──────────────────────────────────────────────────────────┘
Testing ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 83/83 0:02:19 • 0:00:00 0.66it/s
[?25h[2024-05-29 04:22:59,545][src.utils.logging_utils][INFO] - Closing loggers...
[2024-05-29 04:22:59,545][src.utils.logging_utils][INFO] - Closing wandb!