Initial Commit
Browse files- README.md +28 -25
- config.json +1 -1
- eval_results_cardiff.json +1 -1
- model.safetensors +3 -0
- training_args.bin +2 -2
README.md
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---
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license: mit
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base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
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tags:
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This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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- F1: 0.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size:
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- eval_batch_size: 32
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- seed: 66
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 30
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### Training results
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| Training Loss | Epoch
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| No log | 1.
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| No log | 3.
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| No log | 5.
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| No log | 6.
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### Framework versions
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- Transformers 4.
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.5
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- Tokenizers 0.
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---
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library_name: transformers
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license: mit
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base_model: haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only
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tags:
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This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-en-cardiff_eng_only) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 533.0406
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- Accuracy: 0.3444
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- F1: 0.2711
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 8
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- eval_batch_size: 32
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- seed: 66
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 30
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.7391 | 100 | 631.4247 | 0.3302 | 0.2694 |
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| No log | 3.4783 | 200 | 605.5723 | 0.3413 | 0.2651 |
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| No log | 5.2174 | 300 | 589.1194 | 0.3369 | 0.2521 |
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| No log | 6.9565 | 400 | 580.2668 | 0.3501 | 0.2633 |
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| 574.1509 | 8.6957 | 500 | 571.8079 | 0.3254 | 0.2189 |
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| 574.1509 | 10.4348 | 600 | 564.8586 | 0.3360 | 0.2072 |
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| 574.1509 | 12.1739 | 700 | 559.2232 | 0.3417 | 0.2567 |
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| 574.1509 | 13.9130 | 800 | 552.7770 | 0.3391 | 0.2289 |
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| 574.1509 | 15.6522 | 900 | 549.6864 | 0.3333 | 0.2295 |
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| 468.9151 | 17.3913 | 1000 | 545.1831 | 0.3338 | 0.2429 |
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| 468.9151 | 19.1304 | 1100 | 541.3506 | 0.3466 | 0.2794 |
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| 468.9151 | 20.8696 | 1200 | 538.9130 | 0.3355 | 0.2612 |
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| 468.9151 | 22.6087 | 1300 | 537.2876 | 0.3470 | 0.2807 |
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| 468.9151 | 24.3478 | 1400 | 535.7286 | 0.3426 | 0.2346 |
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| 433.9469 | 26.0870 | 1500 | 533.7326 | 0.3492 | 0.2730 |
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| 433.9469 | 27.8261 | 1600 | 533.2730 | 0.3338 | 0.2553 |
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| 433.9469 | 29.5652 | 1700 | 533.0406 | 0.3444 | 0.2711 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.14.5
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- Tokenizers 0.19.1
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config.json
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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.
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"type_vocab_size": 0,
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"vocab_size": 251000
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}
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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": 0,
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"vocab_size": 251000
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}
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eval_results_cardiff.json
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{"arabic": {"f1": 0.
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{"arabic": {"f1": 0.28620417681149485, "accuracy": 0.35747126436781607, "confusion_matrix": [[163, 0, 127], [129, 0, 161], [141, 1, 148]]}, "english": {"f1": 0.3215552226394243, "accuracy": 0.4011494252873563, "confusion_matrix": [[193, 0, 97], [145, 1, 144], [135, 0, 155]]}, "french": {"f1": 0.27630863809500567, "accuracy": 0.34022988505747126, "confusion_matrix": [[163, 0, 127], [125, 3, 162], [160, 0, 130]]}, "german": {"f1": 0.2871860588026614, "accuracy": 0.35747126436781607, "confusion_matrix": [[116, 1, 173], [118, 3, 169], [94, 4, 192]]}, "hindi": {"f1": 0.2716721663906872, "accuracy": 0.33793103448275863, "confusion_matrix": [[108, 1, 181], [82, 3, 205], [106, 1, 183]]}, "italian": {"f1": 0.303020455281475, "accuracy": 0.37701149425287356, "confusion_matrix": [[179, 1, 110], [134, 1, 155], [141, 1, 148]]}, "portuguese": {"f1": 0.30380648608488964, "accuracy": 0.3758620689655172, "confusion_matrix": [[136, 2, 152], [134, 3, 153], [102, 0, 188]]}, "spanish": {"f1": 0.27510022929420136, "accuracy": 0.335632183908046, "confusion_matrix": [[132, 4, 154], [140, 4, 146], [132, 2, 156]]}, "all": {"f1": 0.2876940961781527, "accuracy": 0.35474137931034483, "confusion_matrix": [[1180, 13, 1127], [989, 17, 1314], [1038, 10, 1272]]}}
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model.safetensors
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size 945150428
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training_args.bin
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size 5304
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