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scenario-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only55

Text Classification
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Safetensors
deberta-v2
Generated from Trainer
Inference Endpoints
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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: 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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  - 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-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only55
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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 [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 6.6399
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- - Accuracy: 0.3580
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- - F1: 0.3432
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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 | 1.4612 | 0.3611 | 0.3403 |
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- | 0.929 | 2.1739 | 500 | 1.9354 | 0.3526 | 0.3461 |
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- | 0.929 | 3.2609 | 750 | 2.3423 | 0.3634 | 0.3417 |
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- | 0.3299 | 4.3478 | 1000 | 3.1282 | 0.3719 | 0.3587 |
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- | 0.3299 | 5.4348 | 1250 | 3.0692 | 0.3573 | 0.3467 |
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- | 0.118 | 6.5217 | 1500 | 4.2081 | 0.3573 | 0.3499 |
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- | 0.118 | 7.6087 | 1750 | 4.0268 | 0.3665 | 0.3593 |
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- | 0.0642 | 8.6957 | 2000 | 4.4486 | 0.3642 | 0.3569 |
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- | 0.0642 | 9.7826 | 2250 | 4.3460 | 0.3565 | 0.3480 |
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- | 0.0457 | 10.8696 | 2500 | 4.6662 | 0.3565 | 0.3504 |
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- | 0.0457 | 11.9565 | 2750 | 4.7074 | 0.3688 | 0.3572 |
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- | 0.0236 | 13.0435 | 3000 | 5.0264 | 0.3603 | 0.3501 |
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- | 0.0236 | 14.1304 | 3250 | 5.2291 | 0.3704 | 0.3539 |
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- | 0.0131 | 15.2174 | 3500 | 5.3242 | 0.3681 | 0.3569 |
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- | 0.0131 | 16.3043 | 3750 | 5.5978 | 0.3557 | 0.3309 |
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- | 0.0063 | 17.3913 | 4000 | 5.4396 | 0.3611 | 0.3517 |
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- | 0.0063 | 18.4783 | 4250 | 5.8156 | 0.3627 | 0.3518 |
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- | 0.0038 | 19.5652 | 4500 | 6.0629 | 0.3557 | 0.3480 |
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- | 0.0038 | 20.6522 | 4750 | 6.1920 | 0.3634 | 0.3504 |
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- | 0.0027 | 21.7391 | 5000 | 6.1783 | 0.3588 | 0.3445 |
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- | 0.0027 | 22.8261 | 5250 | 6.3264 | 0.3488 | 0.3392 |
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- | 0.0018 | 23.9130 | 5500 | 6.4320 | 0.3627 | 0.3446 |
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- | 0.0018 | 25.0 | 5750 | 6.5642 | 0.3534 | 0.3381 |
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- | 0.0005 | 26.0870 | 6000 | 6.5669 | 0.3511 | 0.3399 |
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- | 0.0005 | 27.1739 | 6250 | 6.5763 | 0.3573 | 0.3431 |
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- | 0.0001 | 28.2609 | 6500 | 6.5973 | 0.3503 | 0.3400 |
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- | 0.0001 | 29.3478 | 6750 | 6.6399 | 0.3580 | 0.3432 |
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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: microsoft/mdeberta-v3-base
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+ tags:
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+ - generated_from_trainer
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  metrics:
8
  - accuracy
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  - f1
 
 
10
  model-index:
11
  - name: scenario-NON-KD-SCR-COPY-CDF-CL-D2_data-cl-cardiff_cl_only55
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  results: []
 
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  This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 6.8361
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+ - Accuracy: 0.3634
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+ - F1: 0.3600
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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 | 1.4035 | 0.3627 | 0.3384 |
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+ | 0.9258 | 2.1739 | 500 | 1.8269 | 0.3688 | 0.3652 |
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+ | 0.9258 | 3.2609 | 750 | 2.2003 | 0.3696 | 0.3691 |
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+ | 0.3143 | 4.3478 | 1000 | 3.2084 | 0.3850 | 0.3842 |
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+ | 0.3143 | 5.4348 | 1250 | 3.4181 | 0.3719 | 0.3668 |
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+ | 0.1172 | 6.5217 | 1500 | 3.9886 | 0.3688 | 0.3622 |
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+ | 0.1172 | 7.6087 | 1750 | 4.2183 | 0.3650 | 0.3626 |
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+ | 0.0592 | 8.6957 | 2000 | 4.6155 | 0.3665 | 0.3545 |
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+ | 0.0592 | 9.7826 | 2250 | 4.7510 | 0.3727 | 0.3685 |
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+ | 0.0394 | 10.8696 | 2500 | 5.1707 | 0.3688 | 0.3628 |
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+ | 0.0394 | 11.9565 | 2750 | 5.0827 | 0.3681 | 0.3636 |
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+ | 0.0238 | 13.0435 | 3000 | 5.5056 | 0.3665 | 0.3535 |
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+ | 0.0238 | 14.1304 | 3250 | 5.3337 | 0.3704 | 0.3661 |
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+ | 0.0171 | 15.2174 | 3500 | 5.7582 | 0.3735 | 0.3709 |
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+ | 0.0171 | 16.3043 | 3750 | 5.9369 | 0.3665 | 0.3598 |
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+ | 0.011 | 17.3913 | 4000 | 6.0815 | 0.3765 | 0.3719 |
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+ | 0.011 | 18.4783 | 4250 | 6.1316 | 0.3819 | 0.3802 |
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+ | 0.0043 | 19.5652 | 4500 | 6.3789 | 0.3727 | 0.3705 |
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+ | 0.0043 | 20.6522 | 4750 | 6.4273 | 0.3673 | 0.3664 |
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+ | 0.0064 | 21.7391 | 5000 | 6.3039 | 0.3758 | 0.3743 |
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+ | 0.0064 | 22.8261 | 5250 | 6.5675 | 0.3619 | 0.3540 |
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+ | 0.0031 | 23.9130 | 5500 | 6.5657 | 0.3688 | 0.3650 |
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+ | 0.0031 | 25.0 | 5750 | 6.6382 | 0.3696 | 0.3666 |
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+ | 0.0016 | 26.0870 | 6000 | 6.7416 | 0.3681 | 0.3643 |
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+ | 0.0016 | 27.1739 | 6250 | 6.7141 | 0.3711 | 0.3677 |
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+ | 0.0006 | 28.2609 | 6500 | 6.7905 | 0.3642 | 0.3600 |
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+ | 0.0006 | 29.3478 | 6750 | 6.8361 | 0.3634 | 0.3600 |
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  ### Framework versions
eval_results_cardiff.json ADDED
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+ {"arabic": {"f1": 0.4389630214241446, "accuracy": 0.4379310344827586, "confusion_matrix": [[130, 89, 71], [112, 128, 50], [88, 79, 123]]}, "english": {"f1": 0.4592492597592343, "accuracy": 0.46206896551724136, "confusion_matrix": [[167, 85, 38], [126, 98, 66], [95, 58, 137]]}, "french": {"f1": 0.3537532675492514, "accuracy": 0.3632183908045977, "confusion_matrix": [[113, 142, 35], [87, 142, 61], [87, 142, 61]]}, "german": {"f1": 0.5548636674472034, "accuracy": 0.5551724137931034, "confusion_matrix": [[164, 51, 75], [77, 149, 64], [63, 57, 170]]}, "hindi": {"f1": 0.429723755201131, "accuracy": 0.4298850574712644, "confusion_matrix": [[136, 77, 77], [108, 116, 66], [92, 76, 122]]}, "italian": {"f1": 0.4904300744688119, "accuracy": 0.5057471264367817, "confusion_matrix": [[84, 113, 93], [26, 204, 60], [48, 90, 152]]}, "portuguese": {"f1": 0.42424373082442157, "accuracy": 0.435632183908046, "confusion_matrix": [[164, 63, 63], [130, 70, 90], [90, 55, 145]]}, "spanish": {"f1": 0.485055118995332, "accuracy": 0.4908045977011494, "confusion_matrix": [[152, 71, 67], [96, 100, 94], [59, 56, 175]]}, "all": {"f1": 0.45817594583107385, "accuracy": 0.4579022988505747, "confusion_matrix": [[1099, 690, 531], [756, 1016, 548], [631, 617, 1072]]}}
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