End of training

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,109 @@
+---
+license: mit
+base_model: kavg/LiLT-SER-FR
+tags:
+- generated_from_trainer
+datasets:
+- xfun
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: LiLT-SER-FR-SIN
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: xfun
+      type: xfun
+      config: xfun.sin
+      split: validation
+      args: xfun.sin
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7617924528301887
+    - name: Recall
+      type: recall
+      value: 0.7955665024630542
+    - name: F1
+      type: f1
+      value: 0.7783132530120481
+    - name: Accuracy
+      type: accuracy
+      value: 0.8647776686772338
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# LiLT-SER-FR-SIN
+
+This model is a fine-tuned version of [kavg/LiLT-SER-FR](https://huggingface.co/kavg/LiLT-SER-FR) on the xfun dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2426
+- Precision: 0.7618
+- Recall: 0.7956
+- F1: 0.7783
+- Accuracy: 0.8648
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 10000
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0057        | 21.74  | 500   | 0.8019          | 0.6884    | 0.7020 | 0.6951 | 0.8582   |
+| 0.008         | 43.48  | 1000  | 1.0139          | 0.6963    | 0.7623 | 0.7278 | 0.8648   |
+| 0.0006        | 65.22  | 1500  | 0.9878          | 0.7090    | 0.7562 | 0.7318 | 0.8592   |
+| 0.0038        | 86.96  | 2000  | 1.2269          | 0.7104    | 0.7401 | 0.7250 | 0.8373   |
+| 0.001         | 108.7  | 2500  | 0.9751          | 0.7276    | 0.7697 | 0.7481 | 0.8707   |
+| 0.0004        | 130.43 | 3000  | 1.0918          | 0.7479    | 0.7672 | 0.7574 | 0.8538   |
+| 0.0003        | 152.17 | 3500  | 1.0782          | 0.7102    | 0.7635 | 0.7359 | 0.8604   |
+| 0.0           | 173.91 | 4000  | 1.0515          | 0.7402    | 0.7894 | 0.7640 | 0.8704   |
+| 0.0001        | 195.65 | 4500  | 1.2154          | 0.7373    | 0.7709 | 0.7538 | 0.8419   |
+| 0.0           | 217.39 | 5000  | 1.1026          | 0.7411    | 0.7722 | 0.7563 | 0.8642   |
+| 0.0001        | 239.13 | 5500  | 1.0594          | 0.7262    | 0.7512 | 0.7385 | 0.8576   |
+| 0.0           | 260.87 | 6000  | 1.1103          | 0.7377    | 0.7759 | 0.7563 | 0.8609   |
+| 0.0           | 282.61 | 6500  | 1.1591          | 0.7267    | 0.7599 | 0.7429 | 0.8610   |
+| 0.0           | 304.35 | 7000  | 1.2382          | 0.7574    | 0.7537 | 0.7556 | 0.8562   |
+| 0.0           | 326.09 | 7500  | 1.2027          | 0.7485    | 0.7882 | 0.7678 | 0.8578   |
+| 0.0001        | 347.83 | 8000  | 1.1492          | 0.7433    | 0.7808 | 0.7616 | 0.8659   |
+| 0.0002        | 369.57 | 8500  | 1.1924          | 0.7570    | 0.7980 | 0.7770 | 0.8655   |
+| 0.0           | 391.3  | 9000  | 1.2426          | 0.7618    | 0.7956 | 0.7783 | 0.8648   |
+| 0.0           | 413.04 | 9500  | 1.3078          | 0.7620    | 0.7808 | 0.7713 | 0.8597   |
+| 0.0           | 434.78 | 10000 | 1.3219          | 0.7639    | 0.7771 | 0.7705 | 0.8579   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.1

config.json

@@ -0,0 +1,48 @@
+{
+  "_name_or_path": "kavg/LiLT-SER-FR",
+  "architectures": [
+    "LiltForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "channel_shrink_ratio": 4,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-QUESTION",
+    "2": "B-ANSWER",
+    "3": "B-HEADER",
+    "4": "I-ANSWER",
+    "5": "I-QUESTION",
+    "6": "I-HEADER"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-ANSWER": 2,
+    "B-HEADER": 3,
+    "B-QUESTION": 1,
+    "I-ANSWER": 4,
+    "I-HEADER": 6,
+    "I-QUESTION": 5,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_2d_position_embeddings": 1024,
+  "max_position_embeddings": 514,
+  "model_type": "lilt",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.38.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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special_tokens_map.json

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+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
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+    "lstrip": false,
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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tokenizer_config.json

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+{
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+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "special": true
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+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 512,
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

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