Initial Commit

README.md

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+---
+library_name: transformers
+license: mit
+base_model: haryoaw/scenario-TCR-NER_data-univner_half
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: scenario-non-kd-po-ner-full-xlmr_data-univner_half66
+  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_half66
+
+This model is a fine-tuned version of [haryoaw/scenario-TCR-NER_data-univner_half](https://huggingface.co/haryoaw/scenario-TCR-NER_data-univner_half) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1331
+- Precision: 0.8406
+- Recall: 0.8491
+- F1: 0.8448
+- 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 |
+|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0102        | 0.5828  | 500   | 0.0979          | 0.8297    | 0.8550 | 0.8422 | 0.9832   |
+| 0.0109        | 1.1655  | 1000  | 0.0889          | 0.8346    | 0.8466 | 0.8406 | 0.9835   |
+| 0.0084        | 1.7483  | 1500  | 0.0932          | 0.8491    | 0.8462 | 0.8477 | 0.9839   |
+| 0.0075        | 2.3310  | 2000  | 0.0919          | 0.8434    | 0.8437 | 0.8436 | 0.9835   |
+| 0.0072        | 2.9138  | 2500  | 0.1043          | 0.8278    | 0.8380 | 0.8329 | 0.9826   |
+| 0.0058        | 3.4965  | 3000  | 0.1020          | 0.8370    | 0.8468 | 0.8419 | 0.9832   |
+| 0.0059        | 4.0793  | 3500  | 0.1030          | 0.8467    | 0.8458 | 0.8463 | 0.9839   |
+| 0.005         | 4.6620  | 4000  | 0.1182          | 0.8492    | 0.8326 | 0.8408 | 0.9830   |
+| 0.005         | 5.2448  | 4500  | 0.1141          | 0.8235    | 0.8510 | 0.8370 | 0.9821   |
+| 0.0044        | 5.8275  | 5000  | 0.1184          | 0.8273    | 0.8572 | 0.8420 | 0.9828   |
+| 0.0045        | 6.4103  | 5500  | 0.1213          | 0.8417    | 0.8494 | 0.8455 | 0.9833   |
+| 0.0048        | 6.9930  | 6000  | 0.1126          | 0.8413    | 0.8413 | 0.8413 | 0.9835   |
+| 0.0043        | 7.5758  | 6500  | 0.1240          | 0.8363    | 0.8472 | 0.8417 | 0.9830   |
+| 0.0036        | 8.1585  | 7000  | 0.1185          | 0.8470    | 0.8450 | 0.8460 | 0.9838   |
+| 0.0032        | 8.7413  | 7500  | 0.1249          | 0.8338    | 0.8391 | 0.8365 | 0.9828   |
+| 0.0022        | 9.3240  | 8000  | 0.1260          | 0.8351    | 0.8499 | 0.8425 | 0.9835   |
+| 0.003         | 9.9068  | 8500  | 0.1208          | 0.8273    | 0.8420 | 0.8346 | 0.9827   |
+| 0.0024        | 10.4895 | 9000  | 0.1216          | 0.8451    | 0.8463 | 0.8457 | 0.9836   |
+| 0.0027        | 11.0723 | 9500  | 0.1214          | 0.8410    | 0.8390 | 0.8400 | 0.9832   |
+| 0.0019        | 11.6550 | 10000 | 0.1234          | 0.8419    | 0.8458 | 0.8438 | 0.9833   |
+| 0.0023        | 12.2378 | 10500 | 0.1289          | 0.8339    | 0.8502 | 0.8420 | 0.9830   |
+| 0.0019        | 12.8205 | 11000 | 0.1286          | 0.8400    | 0.8401 | 0.8401 | 0.9832   |
+| 0.002         | 13.4033 | 11500 | 0.1331          | 0.8406    | 0.8491 | 0.8448 | 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_half",
+  "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": 0.6515151515151515, "recall": 0.8775510204081632, "f1": 0.7478260869565216, "accuracy": 0.9783783783783784}, "en_pud": {"precision": 0.8212237093690249, "recall": 0.7990697674418604, "f1": 0.8099952852428101, "accuracy": 0.9802134491877598}, "de_pud": {"precision": 0.8014981273408239, "recall": 0.8238691049085659, "f1": 0.8125296630280019, "accuracy": 0.9786226618536402}, "pt_pud": {"precision": 0.8650137741046832, "recall": 0.8571428571428571, "f1": 0.8610603290676416, "accuracy": 0.9854317084632802}, "ru_pud": {"precision": 0.7129798903107861, "recall": 0.752895752895753, "f1": 0.732394366197183, "accuracy": 0.9727202273314389}, "sv_pud": {"precision": 0.859086491739553, "recall": 0.859086491739553, "f1": 0.859086491739553, "accuracy": 0.9858985112182848}, "tl_trg": {"precision": 0.9166666666666666, "recall": 0.9565217391304348, "f1": 0.9361702127659574, "accuracy": 0.9959128065395095}, "tl_ugnayan": {"precision": 0.6923076923076923, "recall": 0.8181818181818182, "f1": 0.7500000000000001, "accuracy": 0.9808568824065633}, "zh_gsd": {"precision": 0.8350785340314136, "recall": 0.8318122555410691, "f1": 0.8334421946440235, "accuracy": 0.9779387279387279}, "zh_gsdsimp": {"precision": 0.8398950131233596, "recall": 0.8387942332896461, "f1": 0.839344262295082, "accuracy": 0.9781884781884782}, "hr_set": {"precision": 0.9279151943462898, "recall": 0.9358517462580185, "f1": 0.9318665720369056, "accuracy": 0.9912613355317395}, "da_ddt": {"precision": 0.8275058275058275, "recall": 0.7941834451901566, "f1": 0.8105022831050228, "accuracy": 0.9857328145265889}, "en_ewt": {"precision": 0.8248587570621468, "recall": 0.8051470588235294, "f1": 0.8148837209302325, "accuracy": 0.9815914252699526}, "pt_bosque": {"precision": 0.8616636528028933, "recall": 0.7843621399176954, "f1": 0.8211977595863852, "accuracy": 0.982393855962904}, "sr_set": {"precision": 0.9475566150178785, "recall": 0.9386068476977568, "f1": 0.9430604982206405, "accuracy": 0.9908939672533054}, "sk_snk": {"precision": 0.7965554359526372, "recall": 0.8087431693989071, "f1": 0.8026030368763557, "accuracy": 0.9722047738693468}, "sv_talbanken": {"precision": 0.8786407766990292, "recall": 0.923469387755102, "f1": 0.900497512437811, "accuracy": 0.9979388526279629}}

model.safetensors

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training_args.bin

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