Initial Commit

README.md

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+---
+library_name: transformers
+license: mit
+base_model: haryoaw/scenario-TCR-NER_data-univner_en
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: scenario-non-kd-po-ner-full-xlmr_data-univner_en66
+  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. -->
+
+# scenario-non-kd-po-ner-full-xlmr_data-univner_en66
+
+This model is a fine-tuned version of [haryoaw/scenario-TCR-NER_data-univner_en](https://huggingface.co/haryoaw/scenario-TCR-NER_data-univner_en) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1477
+- Precision: 0.8101
+- Recall: 0.7992
+- F1: 0.8046
+- Accuracy: 0.9836
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 66
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0036        | 1.2755  | 500   | 0.1194          | 0.8112    | 0.7785 | 0.7945 | 0.9831   |
+| 0.0035        | 2.5510  | 1000  | 0.1172          | 0.7899    | 0.8137 | 0.8016 | 0.9838   |
+| 0.0029        | 3.8265  | 1500  | 0.1173          | 0.7804    | 0.7909 | 0.7856 | 0.9822   |
+| 0.0019        | 5.1020  | 2000  | 0.1175          | 0.7907    | 0.7940 | 0.7924 | 0.9841   |
+| 0.0018        | 6.3776  | 2500  | 0.1271          | 0.7935    | 0.7836 | 0.7885 | 0.9830   |
+| 0.0021        | 7.6531  | 3000  | 0.1281          | 0.7975    | 0.7909 | 0.7942 | 0.9837   |
+| 0.0012        | 8.9286  | 3500  | 0.1170          | 0.7908    | 0.8023 | 0.7965 | 0.9843   |
+| 0.0018        | 10.2041 | 4000  | 0.1324          | 0.8084    | 0.7950 | 0.8017 | 0.9840   |
+| 0.0011        | 11.4796 | 4500  | 0.1304          | 0.7926    | 0.8188 | 0.8055 | 0.9839   |
+| 0.0007        | 12.7551 | 5000  | 0.1370          | 0.7958    | 0.7867 | 0.7913 | 0.9838   |
+| 0.0011        | 14.0306 | 5500  | 0.1297          | 0.7867    | 0.8095 | 0.7980 | 0.9837   |
+| 0.0012        | 15.3061 | 6000  | 0.1254          | 0.7772    | 0.8126 | 0.7945 | 0.9830   |
+| 0.0007        | 16.5816 | 6500  | 0.1374          | 0.8304    | 0.7909 | 0.8102 | 0.9831   |
+| 0.0006        | 17.8571 | 7000  | 0.1369          | 0.7903    | 0.8116 | 0.8008 | 0.9832   |
+| 0.0003        | 19.1327 | 7500  | 0.1379          | 0.7961    | 0.8043 | 0.8002 | 0.9841   |
+| 0.0003        | 20.4082 | 8000  | 0.1365          | 0.7953    | 0.8002 | 0.7977 | 0.9838   |
+| 0.0004        | 21.6837 | 8500  | 0.1458          | 0.7879    | 0.8230 | 0.8051 | 0.9835   |
+| 0.0004        | 22.9592 | 9000  | 0.1475          | 0.8101    | 0.7992 | 0.8046 | 0.9835   |
+| 0.0004        | 24.2347 | 9500  | 0.1405          | 0.7931    | 0.8054 | 0.7992 | 0.9837   |
+| 0.0001        | 25.5102 | 10000 | 0.1391          | 0.7949    | 0.8147 | 0.8047 | 0.9843   |
+| 0.0002        | 26.7857 | 10500 | 0.1432          | 0.8067    | 0.8033 | 0.8050 | 0.9840   |
+| 0.0002        | 28.0612 | 11000 | 0.1439          | 0.8067    | 0.7992 | 0.8029 | 0.9836   |
+| 0.0001        | 29.3367 | 11500 | 0.1477          | 0.8101    | 0.7992 | 0.8046 | 0.9836   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.14.5
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "haryoaw/scenario-TCR-NER_data-univner_en",
+  "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": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

eval_result_ner.json

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+{"ceb_gja": {"precision": 0.6031746031746031, "recall": 0.7755102040816326, "f1": 0.6785714285714285, "accuracy": 0.9714285714285714}, "en_pud": {"precision": 0.8031496062992126, "recall": 0.7590697674418605, "f1": 0.7804878048780488, "accuracy": 0.9790800906686815}, "de_pud": {"precision": 0.7858627858627859, "recall": 0.7276227141482194, "f1": 0.7556221889055473, "accuracy": 0.9738877689747316}, "pt_pud": {"precision": 0.8387734915924827, "recall": 0.7716105550500455, "f1": 0.8037914691943128, "accuracy": 0.9798778143290469}, "ru_pud": {"precision": 0.7028688524590164, "recall": 0.6621621621621622, "f1": 0.6819085487077535, "accuracy": 0.9662102815809869}, "sv_pud": {"precision": 0.8563995837669095, "recall": 0.7998056365403304, "f1": 0.8271356783919598, "accuracy": 0.981862025581883}, "tl_trg": {"precision": 0.9047619047619048, "recall": 0.8260869565217391, "f1": 0.8636363636363636, "accuracy": 0.9931880108991825}, "tl_ugnayan": {"precision": 0.7027027027027027, "recall": 0.7878787878787878, "f1": 0.7428571428571429, "accuracy": 0.9817684594348223}, "zh_gsd": {"precision": 0.5692599620493358, "recall": 0.39113428943937417, "f1": 0.463678516228748, "accuracy": 0.9309024309024309}, "zh_gsdsimp": {"precision": 0.5611650485436893, "recall": 0.37876802096985585, "f1": 0.4522691705790297, "accuracy": 0.9329004329004329}, "hr_set": {"precision": 0.8473344103392568, "recall": 0.7476835352815395, "f1": 0.7943960620976903, "accuracy": 0.972835943940643}, "da_ddt": {"precision": 0.8027027027027027, "recall": 0.6644295302013423, "f1": 0.7270501835985312, "accuracy": 0.9795470418038511}, "en_ewt": {"precision": 0.8431372549019608, "recall": 0.7509191176470589, "f1": 0.7943607194944093, "accuracy": 0.978363947882217}, "pt_bosque": {"precision": 0.8260869565217391, "recall": 0.6567901234567901, "f1": 0.731774415405777, "accuracy": 0.9702941602666281}, "sr_set": {"precision": 0.8490813648293963, "recall": 0.7638724911452184, "f1": 0.8042262274704784, "accuracy": 0.9670781893004116}, "sk_snk": {"precision": 0.7160342717258262, "recall": 0.639344262295082, "f1": 0.6755196304849884, "accuracy": 0.9558731155778895}, "sv_talbanken": {"precision": 0.8613861386138614, "recall": 0.8877551020408163, "f1": 0.8743718592964823, "accuracy": 0.9973008784413799}}

model.safetensors

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training_args.bin

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