Initial Commit
Browse files- README.md +60 -60
- config.json +14 -21
- eval_result_ner.json +1 -1
- model.safetensors +2 -2
- training_args.bin +1 -1
README.md
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---
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base_model: microsoft/mdeberta-v3-base
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library_name: transformers
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license: mit
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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tags:
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- generated_from_trainer
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model-index:
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- name: scenario-kd-pre-ner-full_data-univner_full44
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results: []
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# scenario-kd-pre-ner-full_data-univner_full44
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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### Framework versions
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---
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library_name: transformers
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license: mit
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base_model: FacebookAI/xlm-roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: scenario-kd-pre-ner-full_data-univner_full44
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results: []
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# scenario-kd-pre-ner-full_data-univner_full44
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4381
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- Precision: 0.8004
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- Recall: 0.7801
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- F1: 0.7902
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- Accuracy: 0.9786
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 1.4593 | 0.5828 | 500 | 0.8367 | 0.6935 | 0.6559 | 0.6742 | 0.9682 |
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| 0.7232 | 1.1655 | 1000 | 0.7569 | 0.7339 | 0.6980 | 0.7155 | 0.9724 |
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| 0.594 | 1.7483 | 1500 | 0.6330 | 0.7335 | 0.7451 | 0.7392 | 0.9741 |
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| 0.4986 | 2.3310 | 2000 | 0.6003 | 0.7291 | 0.7552 | 0.7419 | 0.9746 |
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| 0.446 | 2.9138 | 2500 | 0.5729 | 0.7403 | 0.7601 | 0.7501 | 0.9747 |
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| 0.385 | 3.4965 | 3000 | 0.5584 | 0.7441 | 0.7617 | 0.7528 | 0.9757 |
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| 0.3605 | 4.0793 | 3500 | 0.5602 | 0.7615 | 0.7575 | 0.7595 | 0.9758 |
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| 0.3172 | 4.6620 | 4000 | 0.5417 | 0.7546 | 0.7725 | 0.7634 | 0.9764 |
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| 0.3061 | 5.2448 | 4500 | 0.5329 | 0.7884 | 0.7485 | 0.7680 | 0.9769 |
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| 0.2856 | 5.8275 | 5000 | 0.5194 | 0.7837 | 0.7618 | 0.7726 | 0.9769 |
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| 0.2642 | 6.4103 | 5500 | 0.5154 | 0.7622 | 0.7780 | 0.7700 | 0.9765 |
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| 0.2592 | 6.9930 | 6000 | 0.5193 | 0.7882 | 0.7572 | 0.7724 | 0.9764 |
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| 0.2401 | 7.5758 | 6500 | 0.5123 | 0.7727 | 0.7599 | 0.7663 | 0.9763 |
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| 0.2344 | 8.1585 | 7000 | 0.4987 | 0.7742 | 0.7736 | 0.7739 | 0.9771 |
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| 0.2234 | 8.7413 | 7500 | 0.4914 | 0.7894 | 0.7640 | 0.7764 | 0.9777 |
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| 0.2131 | 9.3240 | 8000 | 0.4856 | 0.7691 | 0.7827 | 0.7758 | 0.9770 |
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| 0.2089 | 9.9068 | 8500 | 0.4898 | 0.7895 | 0.7655 | 0.7773 | 0.9773 |
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| 0.1972 | 10.4895 | 9000 | 0.4860 | 0.7828 | 0.7726 | 0.7777 | 0.9775 |
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| 0.1942 | 11.0723 | 9500 | 0.4787 | 0.7807 | 0.7807 | 0.7807 | 0.9776 |
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| 0.1854 | 11.6550 | 10000 | 0.4858 | 0.7916 | 0.7635 | 0.7773 | 0.9771 |
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| 0.183 | 12.2378 | 10500 | 0.4739 | 0.7924 | 0.7800 | 0.7862 | 0.9779 |
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| 0.1781 | 12.8205 | 11000 | 0.4741 | 0.7990 | 0.7661 | 0.7822 | 0.9779 |
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| 0.1704 | 13.4033 | 11500 | 0.4622 | 0.7937 | 0.7719 | 0.7826 | 0.9784 |
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| 0.1698 | 13.9860 | 12000 | 0.4650 | 0.8000 | 0.7657 | 0.7825 | 0.9777 |
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| 0.1635 | 14.5688 | 12500 | 0.4604 | 0.7913 | 0.7778 | 0.7845 | 0.9782 |
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| 0.1605 | 15.1515 | 13000 | 0.4656 | 0.7990 | 0.7605 | 0.7793 | 0.9774 |
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| 0.1559 | 15.7343 | 13500 | 0.4638 | 0.8001 | 0.7658 | 0.7826 | 0.9778 |
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| 0.1531 | 16.3170 | 14000 | 0.4550 | 0.7991 | 0.7735 | 0.7861 | 0.9780 |
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| 0.1519 | 16.8998 | 14500 | 0.4606 | 0.7949 | 0.7735 | 0.7841 | 0.9780 |
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| 0.1482 | 17.4825 | 15000 | 0.4483 | 0.7947 | 0.7831 | 0.7889 | 0.9787 |
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| 0.1449 | 18.0653 | 15500 | 0.4521 | 0.7947 | 0.7722 | 0.7833 | 0.9780 |
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| 0.1407 | 18.6480 | 16000 | 0.4508 | 0.7932 | 0.7728 | 0.7829 | 0.9780 |
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| 0.1415 | 19.2308 | 16500 | 0.4484 | 0.8031 | 0.7728 | 0.7876 | 0.9785 |
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| 0.1385 | 19.8135 | 17000 | 0.4461 | 0.7991 | 0.7774 | 0.7881 | 0.9785 |
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| 0.1358 | 20.3963 | 17500 | 0.4488 | 0.7970 | 0.7756 | 0.7862 | 0.9783 |
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| 0.1358 | 20.9790 | 18000 | 0.4431 | 0.8006 | 0.7772 | 0.7887 | 0.9787 |
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| 0.1325 | 21.5618 | 18500 | 0.4395 | 0.8053 | 0.7768 | 0.7908 | 0.9785 |
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| 0.1322 | 22.1445 | 19000 | 0.4461 | 0.7960 | 0.7725 | 0.7841 | 0.9780 |
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| 0.1296 | 22.7273 | 19500 | 0.4401 | 0.7988 | 0.7746 | 0.7866 | 0.9781 |
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| 0.1288 | 23.3100 | 20000 | 0.4416 | 0.7961 | 0.7690 | 0.7823 | 0.9781 |
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| 0.1271 | 23.8928 | 20500 | 0.4450 | 0.8024 | 0.7673 | 0.7844 | 0.9781 |
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| 0.1246 | 24.4755 | 21000 | 0.4403 | 0.7967 | 0.7703 | 0.7833 | 0.9782 |
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| 0.1254 | 25.0583 | 21500 | 0.4403 | 0.7976 | 0.7742 | 0.7857 | 0.9782 |
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| 0.1231 | 25.6410 | 22000 | 0.4438 | 0.8057 | 0.7694 | 0.7872 | 0.9783 |
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| 0.1228 | 26.2238 | 22500 | 0.4365 | 0.8058 | 0.7741 | 0.7896 | 0.9785 |
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| 0.1224 | 26.8065 | 23000 | 0.4325 | 0.7995 | 0.7806 | 0.7899 | 0.9787 |
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| 0.1211 | 27.3893 | 23500 | 0.4402 | 0.8058 | 0.7676 | 0.7862 | 0.9782 |
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| 0.1202 | 27.9720 | 24000 | 0.4378 | 0.8017 | 0.7689 | 0.7849 | 0.9784 |
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| 0.1201 | 28.5548 | 24500 | 0.4331 | 0.8000 | 0.7784 | 0.7890 | 0.9786 |
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| 0.12 | 29.1375 | 25000 | 0.4317 | 0.7999 | 0.7794 | 0.7895 | 0.9787 |
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| 0.1194 | 29.7203 | 25500 | 0.4381 | 0.8004 | 0.7801 | 0.7902 | 0.9786 |
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### Framework versions
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"attention_probs_dropout_prob": 0.1,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"LABEL_5": 5,
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"LABEL_6": 6
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},
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"layer_norm_eps": 1e-
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"max_position_embeddings":
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"model_type": "deberta-v2",
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"norm_rel_ebd": "layer_norm",
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"pooler_hidden_size": 768,
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"pos_att_type": [
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"c2p"
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],
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"position_biased_input": false,
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"position_buckets": 256,
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"relative_attention": true,
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"share_att_key": true,
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"torch_dtype": "float32",
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"transformers_version": "4.44.2",
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"type_vocab_size":
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}
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{
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"_name_or_path": "FacebookAI/xlm-roberta-base",
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"architectures": [
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"XLMRobertaForTokenClassificationKD"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"LABEL_5": 5,
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"LABEL_6": 6
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 6,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.44.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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eval_result_ner.json
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{"ceb_gja": {"precision": 0.
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{"ceb_gja": {"precision": 0.6140350877192983, "recall": 0.7142857142857143, "f1": 0.6603773584905661, "accuracy": 0.9691119691119691}, "en_pud": {"precision": 0.7703488372093024, "recall": 0.7395348837209302, "f1": 0.7546274323682961, "accuracy": 0.976435587457499}, "de_pud": {"precision": 0.7527638190954774, "recall": 0.7208854667949952, "f1": 0.7364798426745329, "accuracy": 0.9719188036191458}, "pt_pud": {"precision": 0.8152380952380952, "recall": 0.7788898999090081, "f1": 0.796649604467194, "accuracy": 0.9806895373178963}, "ru_pud": {"precision": 0.6679499518768046, "recall": 0.6698841698841699, "f1": 0.6689156626506023, "accuracy": 0.9669852751227073}, "sv_pud": {"precision": 0.8302469135802469, "recall": 0.7842565597667639, "f1": 0.8065967016491754, "accuracy": 0.9807611658628643}, "tl_trg": {"precision": 0.7916666666666666, "recall": 0.8260869565217391, "f1": 0.8085106382978724, "accuracy": 0.989100817438692}, "tl_ugnayan": {"precision": 0.6774193548387096, "recall": 0.6363636363636364, "f1": 0.65625, "accuracy": 0.9726526891522334}, "zh_gsd": {"precision": 0.8073394495412844, "recall": 0.803129074315515, "f1": 0.8052287581699348, "accuracy": 0.9725274725274725}, "zh_gsdsimp": {"precision": 0.8204081632653061, "recall": 0.7903014416775884, "f1": 0.8050734312416555, "accuracy": 0.9723609723609724}, "hr_set": {"precision": 0.8908450704225352, "recall": 0.9016393442622951, "f1": 0.8962097059865392, "accuracy": 0.9874690849134378}, "da_ddt": {"precision": 0.8152709359605911, "recall": 0.7404921700223713, "f1": 0.7760844079718641, "accuracy": 0.9831387808041504}, "en_ewt": {"precision": 0.8059701492537313, "recall": 0.7444852941176471, "f1": 0.7740086000955566, "accuracy": 0.9770888950870622}, "pt_bosque": {"precision": 0.7911985018726592, "recall": 0.6954732510288066, "f1": 0.7402540516863776, "accuracy": 0.97616287494566}, "sr_set": {"precision": 0.9170616113744076, "recall": 0.9138134592680047, "f1": 0.9154346540508574, "accuracy": 0.9883547850450923}, "sk_snk": {"precision": 0.7004716981132075, "recall": 0.6491803278688525, "f1": 0.6738513896766876, "accuracy": 0.956265703517588}, "sv_talbanken": {"precision": 0.8374384236453202, "recall": 0.8673469387755102, "f1": 0.8521303258145363, "accuracy": 0.997202728566521}}
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model.safetensors
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training_args.bin
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