lewtun HF staff commited on
Commit
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End of training

Browse files
README.md CHANGED
@@ -7,20 +7,20 @@ metrics:
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  - accuracy
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  - f1
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  model-index:
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- - name: kato-dummy
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # kato-dummy
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  This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5742
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- - Accuracy: 0.647
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- - F1: 0.6466
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  ## Model description
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@@ -39,7 +39,7 @@ More information needed
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  ### Training hyperparameters
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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: 4
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  - eval_batch_size: 4
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  - seed: 42
@@ -54,10 +54,10 @@ The following hyperparameters were used during training:
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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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- | 0.6472 | 1.0 | 250 | 0.6111 | 0.5915 | 0.4867 |
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- | 0.5499 | 2.0 | 500 | 0.5742 | 0.647 | 0.6466 |
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  ### Framework versions
 
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  - accuracy
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  - f1
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  model-index:
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+ - name: deberta-v3-large-classifier
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # deberta-v3-large-classifier
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  This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4924
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+ - Accuracy: 0.7255
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+ - F1: 0.7230
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 8e-06
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
 
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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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+ | 0.4852 | 1.0 | 15898 | 0.4908 | 0.7223 | 0.7143 |
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+ | 0.4751 | 2.0 | 31796 | 0.4924 | 0.7255 | 0.7230 |
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  ### Framework versions
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