Training in progress epoch 0
Browse files- README.md +53 -0
- config.json +83 -0
- logs/train/events.out.tfevents.1651755288.bb3a84e6bfa0.600.0.v2 +3 -0
- logs/train/events.out.tfevents.1651755309.bb3a84e6bfa0.profile-empty +3 -0
- logs/train/plugins/profile/2022_05_05_12_55_09/bb3a84e6bfa0.input_pipeline.pb +3 -0
- logs/train/plugins/profile/2022_05_05_12_55_09/bb3a84e6bfa0.kernel_stats.pb +3 -0
- logs/train/plugins/profile/2022_05_05_12_55_09/bb3a84e6bfa0.memory_profile.json.gz +3 -0
- logs/train/plugins/profile/2022_05_05_12_55_09/bb3a84e6bfa0.overview_page.pb +3 -0
- logs/train/plugins/profile/2022_05_05_12_55_09/bb3a84e6bfa0.tensorflow_stats.pb +3 -0
- logs/train/plugins/profile/2022_05_05_12_55_09/bb3a84e6bfa0.trace.json.gz +3 -0
- logs/train/plugins/profile/2022_05_05_12_55_09/bb3a84e6bfa0.xplane.pb +3 -0
- logs/validation/events.out.tfevents.1651755959.bb3a84e6bfa0.600.1.v2 +3 -0
- special_tokens_map.json +1 -0
- tf_model.h5 +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
README.md
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---
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license: mit
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tags:
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- generated_from_keras_callback
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model-index:
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- name: Ruth/gelectra-large-germeval_14
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# Ruth/gelectra-large-germeval_14
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This model is a fine-tuned version of [deepset/gelectra-large](https://huggingface.co/deepset/gelectra-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.1998
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- Validation Loss: 0.0986
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- Epoch: 0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 12750, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
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- training_precision: float32
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### Training results
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| Train Loss | Validation Loss | Epoch |
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|:----------:|:---------------:|:-----:|
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| 0.1998 | 0.0986 | 0 |
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### Framework versions
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- Transformers 4.18.0
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- TensorFlow 2.6.2
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- Datasets 1.18.0
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- Tokenizers 0.12.1
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config.json
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{
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"_name_or_path": "deepset/gelectra-large",
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"architectures": [
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"ElectraForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"embedding_size": 1024,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"id2label": {
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"0": "O",
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"1": "B-LOC",
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"10": "I-ORGderiv",
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"11": "B-ORGpart",
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"12": "I-ORGpart",
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"13": "B-OTH",
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"14": "I-OTH",
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"15": "B-OTHderiv",
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"16": "I-OTHderiv",
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"17": "B-OTHpart",
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"18": "I-OTHpart",
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"19": "B-PER",
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"2": "I-LOC",
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"20": "I-PER",
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"21": "B-PERderiv",
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"22": "I-PERderiv",
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"23": "B-PERpart",
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"24": "I-PERpart",
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"3": "B-LOCderiv",
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"4": "I-LOCderiv",
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"5": "B-LOCpart",
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"6": "I-LOCpart",
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"7": "B-ORG",
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"8": "I-ORG",
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"9": "B-ORGderiv"
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},
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"B-LOC": "1",
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"B-LOCderiv": "3",
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"B-LOCpart": "5",
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"B-ORG": "7",
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"B-ORGderiv": "9",
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"B-ORGpart": "11",
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"B-OTH": "13",
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"B-OTHderiv": "15",
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"B-OTHpart": "17",
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"B-PER": "19",
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"B-PERderiv": "21",
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"B-PERpart": "23",
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"I-LOC": "2",
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"I-LOCderiv": "4",
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"I-LOCpart": "6",
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"I-ORG": "8",
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"I-ORGderiv": "10",
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"I-ORGpart": "12",
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"I-OTH": "14",
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"I-OTHderiv": "16",
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"I-OTHpart": "18",
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"I-PER": "20",
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"I-PERderiv": "22",
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"I-PERpart": "24",
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"O": "0"
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "electra",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"summary_activation": "gelu",
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"summary_last_dropout": 0.1,
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"summary_type": "first",
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"summary_use_proj": true,
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"transformers_version": "4.18.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 31102
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}
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logs/train/events.out.tfevents.1651755288.bb3a84e6bfa0.600.0.v2
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tf_model.h5
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tokenizer.json
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tokenizer_config.json
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{"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": false, "max_len": 512, "special_tokens_map_file": null, "name_or_path": "deepset/gelectra-large", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "ElectraTokenizer"}
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vocab.txt
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