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CS221-deberta-base-finetuned-semeval-aug

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  1. README.md +14 -24
  2. model.safetensors +1 -1
README.md CHANGED
@@ -19,10 +19,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3475
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- - F1: 0.8781
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- - Roc Auc: 0.9070
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- - Accuracy: 0.7651
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | 0.4197 | 1.0 | 277 | 0.3731 | 0.6624 | 0.7504 | 0.4435 |
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- | 0.2694 | 2.0 | 554 | 0.3172 | 0.7734 | 0.8309 | 0.5411 |
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- | 0.1796 | 3.0 | 831 | 0.2815 | 0.7769 | 0.8256 | 0.5890 |
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- | 0.1281 | 4.0 | 1108 | 0.2802 | 0.8120 | 0.8543 | 0.6305 |
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- | 0.0754 | 5.0 | 1385 | 0.2998 | 0.8177 | 0.8565 | 0.6495 |
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- | 0.067 | 6.0 | 1662 | 0.2926 | 0.8367 | 0.8755 | 0.6838 |
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- | 0.0303 | 7.0 | 1939 | 0.2977 | 0.8409 | 0.8750 | 0.7010 |
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- | 0.009 | 8.0 | 2216 | 0.3252 | 0.8474 | 0.8777 | 0.7091 |
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- | 0.0114 | 9.0 | 2493 | 0.3181 | 0.8539 | 0.8899 | 0.7281 |
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- | 0.006 | 10.0 | 2770 | 0.3390 | 0.8581 | 0.8890 | 0.7344 |
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- | 0.0023 | 11.0 | 3047 | 0.3407 | 0.8646 | 0.8934 | 0.7353 |
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- | 0.0022 | 12.0 | 3324 | 0.3453 | 0.8674 | 0.8991 | 0.7525 |
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- | 0.0031 | 13.0 | 3601 | 0.3488 | 0.8708 | 0.9021 | 0.7507 |
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- | 0.0013 | 14.0 | 3878 | 0.3440 | 0.8736 | 0.9044 | 0.7579 |
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- | 0.0009 | 15.0 | 4155 | 0.3475 | 0.8781 | 0.9070 | 0.7651 |
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- | 0.0026 | 16.0 | 4432 | 0.3455 | 0.8767 | 0.9057 | 0.7651 |
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- | 0.0008 | 17.0 | 4709 | 0.3504 | 0.8755 | 0.9053 | 0.7615 |
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- | 0.0009 | 18.0 | 4986 | 0.3549 | 0.8742 | 0.9043 | 0.7588 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2871
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+ - F1: 0.8364
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+ - Roc Auc: 0.8738
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+ - Accuracy: 0.6387
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.2713 | 1.0 | 139 | 0.3886 | 0.7310 | 0.8051 | 0.4228 |
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+ | 0.2914 | 2.0 | 278 | 0.3337 | 0.7849 | 0.8464 | 0.5248 |
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+ | 0.2201 | 3.0 | 417 | 0.3073 | 0.7995 | 0.8511 | 0.5501 |
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+ | 0.1444 | 4.0 | 556 | 0.3027 | 0.8275 | 0.8727 | 0.6007 |
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+ | 0.0964 | 5.0 | 695 | 0.2871 | 0.8364 | 0.8738 | 0.6387 |
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+ | 0.0536 | 6.0 | 834 | 0.3024 | 0.8432 | 0.8796 | 0.6612 |
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+ | 0.042 | 7.0 | 973 | 0.2909 | 0.8631 | 0.8960 | 0.6920 |
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+ | 0.0334 | 8.0 | 1112 | 0.2976 | 0.8675 | 0.9002 | 0.7037 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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