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loha_fine_tuned_rte_XLMroberta

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  1. README.md +11 -11
  2. adapter_model.safetensors +1 -1
  3. runs/May22_22-03-25_DESKTOP-22QTFDR/events.out.tfevents.1716408207.DESKTOP-22QTFDR.32492.2 +3 -0
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  5. runs/May22_22-07-26_DESKTOP-22QTFDR/events.out.tfevents.1716408449.DESKTOP-22QTFDR.32384.0 +3 -0
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  7. runs/May22_22-09-54_DESKTOP-22QTFDR/events.out.tfevents.1716408595.DESKTOP-22QTFDR.32384.2 +3 -0
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  9. runs/May22_22-11-24_DESKTOP-22QTFDR/events.out.tfevents.1716408685.DESKTOP-22QTFDR.32384.4 +3 -0
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  11. runs/May22_22-13-10_DESKTOP-22QTFDR/events.out.tfevents.1716408792.DESKTOP-22QTFDR.32384.6 +3 -0
  12. runs/May22_22-13-10_DESKTOP-22QTFDR/events.out.tfevents.1716408859.DESKTOP-22QTFDR.32384.7 +3 -0
  13. training_args.bin +1 -1
README.md CHANGED
@@ -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 [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6906
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  - Accuracy: 0.6207
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- - F1: 0.5466
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  ## Model description
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@@ -40,7 +40,7 @@ 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: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -52,14 +52,14 @@ 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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- | 0.7061 | 1.7241 | 50 | 0.7021 | 0.4138 | 0.2422 |
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- | 0.7012 | 3.4483 | 100 | 0.6955 | 0.4138 | 0.2422 |
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- | 0.6902 | 5.1724 | 150 | 0.6970 | 0.4138 | 0.2422 |
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- | 0.6922 | 6.8966 | 200 | 0.6917 | 0.5172 | 0.5087 |
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- | 0.694 | 8.6207 | 250 | 0.6897 | 0.5862 | 0.4333 |
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- | 0.6945 | 10.3448 | 300 | 0.6906 | 0.5517 | 0.4169 |
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- | 0.6926 | 12.0690 | 350 | 0.6903 | 0.5862 | 0.4854 |
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- | 0.6883 | 13.7931 | 400 | 0.6906 | 0.6207 | 0.5466 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.0980
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  - Accuracy: 0.6207
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+ - F1: 0.6090
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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: 0.003
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
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+ | 0.8165 | 1.7241 | 50 | 0.7174 | 0.4828 | 0.3781 |
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+ | 0.7386 | 3.4483 | 100 | 0.6616 | 0.6897 | 0.6523 |
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+ | 0.7293 | 5.1724 | 150 | 0.7683 | 0.5172 | 0.4660 |
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+ | 0.6773 | 6.8966 | 200 | 1.1129 | 0.4483 | 0.4324 |
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+ | 0.4623 | 8.6207 | 250 | 1.7863 | 0.5862 | 0.5892 |
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+ | 0.2532 | 10.3448 | 300 | 2.8440 | 0.5862 | 0.5483 |
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+ | 0.0813 | 12.0690 | 350 | 3.0842 | 0.5517 | 0.5484 |
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+ | 0.0478 | 13.7931 | 400 | 3.0980 | 0.6207 | 0.6090 |
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  ### Framework versions
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