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scenario-MDBT-TCR_data-cl-cardiff_cl_only

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deberta-v2
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  1. README.md +32 -18
  2. eval_results_cardiff.json +1 -1
  3. pytorch_model.bin +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ 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: 4.6543
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- - Accuracy: 0.5131
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- - F1: 0.5145
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  ## Model description
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@@ -40,8 +40,8 @@ More information needed
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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: 64
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- - eval_batch_size: 128
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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
@@ -51,19 +51,33 @@ 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 | 2.17 | 250 | 1.4134 | 0.5069 | 0.5083 |
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- | 0.5524 | 4.35 | 500 | 1.9853 | 0.5208 | 0.5230 |
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- | 0.5524 | 6.52 | 750 | 2.5990 | 0.4853 | 0.4797 |
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- | 0.1315 | 8.7 | 1000 | 2.8603 | 0.4961 | 0.4954 |
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- | 0.1315 | 10.87 | 1250 | 3.1408 | 0.5093 | 0.5099 |
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- | 0.0497 | 13.04 | 1500 | 3.3859 | 0.5177 | 0.5190 |
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- | 0.0497 | 15.22 | 1750 | 3.9204 | 0.5039 | 0.5044 |
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- | 0.0219 | 17.39 | 2000 | 4.0747 | 0.5139 | 0.5160 |
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- | 0.0219 | 19.57 | 2250 | 4.3170 | 0.5139 | 0.5156 |
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- | 0.0133 | 21.74 | 2500 | 4.5924 | 0.5023 | 0.5020 |
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- | 0.0133 | 23.91 | 2750 | 4.6042 | 0.5100 | 0.5114 |
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- | 0.0046 | 26.09 | 3000 | 4.5407 | 0.5147 | 0.5163 |
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- | 0.0046 | 28.26 | 3250 | 4.6543 | 0.5131 | 0.5145 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 4.7992
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+ - Accuracy: 0.5154
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+ - F1: 0.5146
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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: 32
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+ - eval_batch_size: 64
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.09 | 250 | 1.2801 | 0.5069 | 0.5029 |
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+ | 0.7278 | 2.17 | 500 | 1.6260 | 0.5077 | 0.5080 |
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+ | 0.7278 | 3.26 | 750 | 1.6500 | 0.5193 | 0.5209 |
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+ | 0.3512 | 4.35 | 1000 | 2.1813 | 0.5123 | 0.5144 |
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+ | 0.3512 | 5.43 | 1250 | 2.5133 | 0.5154 | 0.5167 |
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+ | 0.1838 | 6.52 | 1500 | 2.6502 | 0.5093 | 0.5093 |
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+ | 0.1838 | 7.61 | 1750 | 3.0408 | 0.5015 | 0.5021 |
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+ | 0.118 | 8.7 | 2000 | 3.3486 | 0.4877 | 0.4822 |
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+ | 0.118 | 9.78 | 2250 | 3.5117 | 0.4923 | 0.4906 |
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+ | 0.072 | 10.87 | 2500 | 3.5966 | 0.5046 | 0.5027 |
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+ | 0.072 | 11.96 | 2750 | 3.3823 | 0.5100 | 0.5121 |
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+ | 0.0545 | 13.04 | 3000 | 3.7627 | 0.5085 | 0.5053 |
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+ | 0.0545 | 14.13 | 3250 | 3.9342 | 0.5108 | 0.5124 |
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+ | 0.0336 | 15.22 | 3500 | 4.2215 | 0.5093 | 0.5061 |
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+ | 0.0336 | 16.3 | 3750 | 4.2219 | 0.5046 | 0.5021 |
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+ | 0.0272 | 17.39 | 4000 | 4.0061 | 0.5208 | 0.5227 |
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+ | 0.0272 | 18.48 | 4250 | 4.3214 | 0.5116 | 0.5074 |
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+ | 0.0198 | 19.57 | 4500 | 4.5333 | 0.5093 | 0.5075 |
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+ | 0.0198 | 20.65 | 4750 | 4.3535 | 0.5247 | 0.5256 |
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+ | 0.0161 | 21.74 | 5000 | 4.5169 | 0.5239 | 0.5238 |
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+ | 0.0161 | 22.83 | 5250 | 4.4982 | 0.5285 | 0.5298 |
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+ | 0.012 | 23.91 | 5500 | 4.5591 | 0.5170 | 0.5186 |
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+ | 0.012 | 25.0 | 5750 | 4.7615 | 0.5085 | 0.5069 |
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+ | 0.0066 | 26.09 | 6000 | 4.8457 | 0.5100 | 0.5079 |
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+ | 0.0066 | 27.17 | 6250 | 4.7872 | 0.5131 | 0.5118 |
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+ | 0.0069 | 28.26 | 6500 | 4.6257 | 0.5301 | 0.5303 |
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+ | 0.0069 | 29.35 | 6750 | 4.7992 | 0.5154 | 0.5146 |
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  ### Framework versions
eval_results_cardiff.json CHANGED
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+ {"arabic": {"f1": 0.5940991842458893, "accuracy": 0.593103448275862, "confusion_matrix": [[146, 113, 31], [48, 215, 27], [20, 115, 155]]}, "english": {"f1": 0.6767487000243078, "accuracy": 0.6793103448275862, "confusion_matrix": [[235, 47, 8], [85, 156, 49], [27, 63, 200]]}, "french": {"f1": 0.5091797893031121, "accuracy": 0.539080459770115, "confusion_matrix": [[147, 134, 9], [23, 259, 8], [33, 194, 63]]}, "german": {"f1": 0.7221885493493773, "accuracy": 0.7229885057471265, "confusion_matrix": [[222, 40, 28], [62, 187, 41], [36, 34, 220]]}, "hindi": {"f1": 0.5148790318312105, "accuracy": 0.5172413793103449, "confusion_matrix": [[155, 64, 71], [88, 123, 79], [65, 53, 172]]}, "italian": {"f1": 0.7147248790960297, "accuracy": 0.7160919540229885, "confusion_matrix": [[183, 63, 44], [19, 242, 29], [28, 64, 198]]}, "portuguese": {"f1": 0.6633915248733473, "accuracy": 0.6632183908045977, "confusion_matrix": [[200, 59, 31], [60, 177, 53], [33, 57, 200]]}, "spanish": {"f1": 0.6573314978575006, "accuracy": 0.6609195402298851, "confusion_matrix": [[218, 46, 26], [80, 147, 63], [18, 62, 210]]}, "all": {"f1": 0.6383252563181864, "accuracy": 0.6364942528735632, "confusion_matrix": [[1526, 562, 232], [471, 1494, 355], [245, 665, 1410]]}}
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