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 +1,75 @@
+---
+language:
+- vi
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+model-index:
+- name: xlm-roberta-large_baseline_words
+  results: []
+---
+
+<!-- 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. -->
+
+# xlm-roberta-large_baseline_words
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the covid19_ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0850
+- Patient Id: 0.9840
+- Name: 0.7711
+- Gender: 0.9767
+- Age: 0.9821
+- Job: 0.8062
+- Location: 0.9570
+- Organization: 0.8784
+- Date: 0.9869
+- Symptom And Disease: 0.8688
+- Transportation: 1.0
+- F1 Macro: 0.9211
+- F1 Micro: 0.9459
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Patient Id | Name   | Gender | Age    | Job    | Location | Organization | Date   | Symptom And Disease | Transportation | F1 Macro | F1 Micro |
+|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:|
+| 0.2002        | 1.0   | 629  | 0.1212          | 0.9160     | 0.8349 | 0.8346 | 0.8122 | 0.5385 | 0.8769   | 0.7201       | 0.9553 | 0.7769              | 0.8587         | 0.8124   | 0.8586   |
+| 0.0557        | 2.0   | 1258 | 0.1025          | 0.9594     | 0.8836 | 0.9533 | 0.9731 | 0.2841 | 0.9228   | 0.8301       | 0.9842 | 0.8545              | 0.9444         | 0.8590   | 0.9191   |
+| 0.038         | 3.0   | 1887 | 0.0804          | 0.9741     | 0.7154 | 0.9732 | 0.9821 | 0.7615 | 0.9372   | 0.8576       | 0.9869 | 0.8461              | 0.9943         | 0.9028   | 0.9309   |
+| 0.0222        | 4.0   | 2516 | 0.0862          | 0.9871     | 0.5567 | 0.9691 | 0.9862 | 0.8207 | 0.9553   | 0.8707       | 0.9847 | 0.8740              | 1.0            | 0.9005   | 0.9398   |
+| 0.0148        | 5.0   | 3145 | 0.0850          | 0.9840     | 0.7711 | 0.9767 | 0.9821 | 0.8062 | 0.9570   | 0.8784       | 0.9869 | 0.8688              | 1.0            | 0.9211   | 0.9459   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "FacebookAI/xlm-roberta-large",
+  "architectures": [
+    "XLMRobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "O",
+    "1": "B-PATIENT_ID",
+    "2": "I-PATIENT_ID",
+    "3": "B-NAME",
+    "4": "I-NAME",
+    "5": "B-GENDER",
+    "6": "I-GENDER",
+    "7": "B-AGE",
+    "8": "I-AGE",
+    "9": "B-JOB",
+    "10": "I-JOB",
+    "11": "B-LOCATION",
+    "12": "I-LOCATION",
+    "13": "B-ORGANIZATION",
+    "14": "I-ORGANIZATION",
+    "15": "B-DATE",
+    "16": "I-DATE",
+    "17": "B-SYMPTOM_AND_DISEASE",
+    "18": "I-SYMPTOM_AND_DISEASE",
+    "19": "B-TRANSPORTATION",
+    "20": "I-TRANSPORTATION"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "B-AGE": 7,
+    "B-DATE": 15,
+    "B-GENDER": 5,
+    "B-JOB": 9,
+    "B-LOCATION": 11,
+    "B-NAME": 3,
+    "B-ORGANIZATION": 13,
+    "B-PATIENT_ID": 1,
+    "B-SYMPTOM_AND_DISEASE": 17,
+    "B-TRANSPORTATION": 19,
+    "I-AGE": 8,
+    "I-DATE": 16,
+    "I-GENDER": 6,
+    "I-JOB": 10,
+    "I-LOCATION": 12,
+    "I-NAME": 4,
+    "I-ORGANIZATION": 14,
+    "I-PATIENT_ID": 2,
+    "I-SYMPTOM_AND_DISEASE": 18,
+    "I-TRANSPORTATION": 20,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

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