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scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only66

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  1. README.md +33 -33
  2. eval_results_cardiff.json +1 -0
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -1,12 +1,12 @@
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  ---
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- base_model: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
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  library_name: transformers
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  license: mit
 
 
 
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  metrics:
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  - accuracy
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  - f1
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- tags:
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- - generated_from_trainer
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  model-index:
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  - name: scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only66
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  results: []
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 5.9844
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- - Accuracy: 0.4483
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- - F1: 0.4469
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  ## Model description
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@@ -52,33 +52,33 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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- | No log | 1.0870 | 250 | 1.1475 | 0.4552 | 0.4538 |
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- | 0.861 | 2.1739 | 500 | 1.5478 | 0.4699 | 0.4682 |
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- | 0.861 | 3.2609 | 750 | 1.9490 | 0.4599 | 0.4584 |
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- | 0.4638 | 4.3478 | 1000 | 2.3832 | 0.4537 | 0.4532 |
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- | 0.4638 | 5.4348 | 1250 | 2.4965 | 0.4568 | 0.4562 |
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- | 0.2113 | 6.5217 | 1500 | 3.4612 | 0.4506 | 0.4511 |
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- | 0.2113 | 7.6087 | 1750 | 3.5718 | 0.4660 | 0.4645 |
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- | 0.1221 | 8.6957 | 2000 | 3.8516 | 0.4367 | 0.4309 |
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- | 0.1221 | 9.7826 | 2250 | 3.9459 | 0.4421 | 0.4349 |
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- | 0.0796 | 10.8696 | 2500 | 4.2407 | 0.4591 | 0.4590 |
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- | 0.0796 | 11.9565 | 2750 | 4.5609 | 0.4498 | 0.4446 |
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- | 0.06 | 13.0435 | 3000 | 4.4842 | 0.4537 | 0.4500 |
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- | 0.06 | 14.1304 | 3250 | 4.6808 | 0.4529 | 0.4497 |
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- | 0.0356 | 15.2174 | 3500 | 5.2708 | 0.4290 | 0.4221 |
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- | 0.0356 | 16.3043 | 3750 | 4.7855 | 0.4383 | 0.4380 |
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- | 0.0282 | 17.3913 | 4000 | 5.2598 | 0.4645 | 0.4644 |
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- | 0.0282 | 18.4783 | 4250 | 5.4851 | 0.4691 | 0.4695 |
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- | 0.0231 | 19.5652 | 4500 | 5.8382 | 0.4406 | 0.4359 |
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- | 0.0231 | 20.6522 | 4750 | 5.4555 | 0.4514 | 0.4501 |
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- | 0.0179 | 21.7391 | 5000 | 5.5153 | 0.4452 | 0.4435 |
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- | 0.0179 | 22.8261 | 5250 | 6.0191 | 0.4421 | 0.4389 |
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- | 0.0108 | 23.9130 | 5500 | 5.7614 | 0.4514 | 0.4490 |
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- | 0.0108 | 25.0 | 5750 | 5.9259 | 0.4522 | 0.4496 |
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- | 0.0087 | 26.0870 | 6000 | 5.9545 | 0.4452 | 0.4438 |
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- | 0.0087 | 27.1739 | 6250 | 5.9292 | 0.4491 | 0.4469 |
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- | 0.0082 | 28.2609 | 6500 | 5.9245 | 0.4630 | 0.4614 |
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- | 0.0082 | 29.3478 | 6750 | 5.9844 | 0.4483 | 0.4469 |
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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: haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only
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+ tags:
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+ - generated_from_trainer
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  metrics:
8
  - accuracy
9
  - f1
 
 
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  model-index:
11
  - name: scenario-NON-KD-PO-COPY-CDF-CL-D2_data-cl-cardiff_cl_only66
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  results: []
 
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  This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-cl-cardiff_cl_only) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 5.9979
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+ - Accuracy: 0.4498
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+ - F1: 0.4497
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0870 | 250 | 1.2493 | 0.4568 | 0.4501 |
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+ | 0.812 | 2.1739 | 500 | 1.5854 | 0.4637 | 0.4628 |
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+ | 0.812 | 3.2609 | 750 | 1.8772 | 0.4614 | 0.4605 |
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+ | 0.4271 | 4.3478 | 1000 | 2.3694 | 0.4414 | 0.4339 |
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+ | 0.4271 | 5.4348 | 1250 | 2.6689 | 0.4537 | 0.4473 |
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+ | 0.1992 | 6.5217 | 1500 | 3.0050 | 0.4537 | 0.4527 |
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+ | 0.1992 | 7.6087 | 1750 | 3.1201 | 0.4468 | 0.4406 |
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+ | 0.1147 | 8.6957 | 2000 | 3.9025 | 0.4360 | 0.4298 |
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+ | 0.1147 | 9.7826 | 2250 | 4.0949 | 0.4390 | 0.4331 |
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+ | 0.0816 | 10.8696 | 2500 | 4.3006 | 0.4306 | 0.4218 |
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+ | 0.0816 | 11.9565 | 2750 | 4.5881 | 0.4606 | 0.4569 |
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+ | 0.0558 | 13.0435 | 3000 | 4.4255 | 0.4576 | 0.4577 |
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+ | 0.0558 | 14.1304 | 3250 | 5.1150 | 0.4606 | 0.4600 |
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+ | 0.0388 | 15.2174 | 3500 | 4.6378 | 0.4568 | 0.4571 |
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+ | 0.0388 | 16.3043 | 3750 | 5.2331 | 0.4498 | 0.4458 |
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+ | 0.0269 | 17.3913 | 4000 | 5.3200 | 0.4491 | 0.4481 |
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+ | 0.0269 | 18.4783 | 4250 | 5.2543 | 0.4599 | 0.4583 |
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+ | 0.0175 | 19.5652 | 4500 | 5.3747 | 0.4552 | 0.4548 |
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+ | 0.0175 | 20.6522 | 4750 | 5.4521 | 0.4460 | 0.4448 |
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+ | 0.0181 | 21.7391 | 5000 | 5.3489 | 0.4606 | 0.4604 |
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+ | 0.0181 | 22.8261 | 5250 | 5.8017 | 0.4552 | 0.4543 |
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+ | 0.0093 | 23.9130 | 5500 | 5.6669 | 0.4560 | 0.4560 |
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+ | 0.0093 | 25.0 | 5750 | 5.5959 | 0.4529 | 0.4517 |
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+ | 0.0076 | 26.0870 | 6000 | 5.8141 | 0.4576 | 0.4554 |
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+ | 0.0076 | 27.1739 | 6250 | 5.8656 | 0.4560 | 0.4556 |
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+ | 0.006 | 28.2609 | 6500 | 5.9365 | 0.4583 | 0.4577 |
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+ | 0.006 | 29.3478 | 6750 | 5.9979 | 0.4498 | 0.4497 |
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  ### Framework versions
eval_results_cardiff.json ADDED
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+ {"arabic": {"f1": 0.5141342857547752, "accuracy": 0.5206896551724138, "confusion_matrix": [[107, 126, 57], [48, 201, 41], [38, 107, 145]]}, "english": {"f1": 0.6247365555013046, "accuracy": 0.6264367816091954, "confusion_matrix": [[209, 51, 30], [89, 147, 54], [27, 74, 189]]}, "french": {"f1": 0.41918287350660394, "accuracy": 0.45632183908045976, "confusion_matrix": [[96, 171, 23], [25, 246, 19], [34, 201, 55]]}, "german": {"f1": 0.676000438545778, "accuracy": 0.6770114942528735, "confusion_matrix": [[175, 56, 59], [44, 207, 39], [43, 40, 207]]}, "hindi": {"f1": 0.444749118764776, "accuracy": 0.44482758620689655, "confusion_matrix": [[141, 87, 62], [87, 128, 75], [71, 101, 118]]}, "italian": {"f1": 0.5974493696744664, "accuracy": 0.5988505747126437, "confusion_matrix": [[140, 65, 85], [24, 192, 74], [30, 71, 189]]}, "portuguese": {"f1": 0.5023028703251889, "accuracy": 0.5103448275862069, "confusion_matrix": [[95, 123, 72], [48, 183, 59], [26, 98, 166]]}, "spanish": {"f1": 0.5520309536600151, "accuracy": 0.5505747126436782, "confusion_matrix": [[130, 126, 34], [50, 178, 62], [27, 92, 171]]}, "all": {"f1": 0.5527935685937077, "accuracy": 0.5531609195402298, "confusion_matrix": [[1108, 801, 411], [410, 1494, 416], [290, 782, 1248]]}}
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