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@@ -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 [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 4.7043
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- - Exact Match: 17.9775
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- - F1: 4.4623
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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: 4.74063606707788e-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 OptimizerNames.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: linear
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  | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|
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- | No log | 1.0 | 11 | 5.2906 | 4.4944 | 5.9189 |
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- | No log | 2.0 | 22 | 5.0704 | 7.8652 | 4.5481 |
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- | No log | 3.0 | 33 | 5.0236 | 24.7191 | 4.0533 |
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- | No log | 4.0 | 44 | 4.9029 | 17.9775 | 4.9746 |
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- | No log | 5.0 | 55 | 4.7043 | 17.9775 | 4.4623 |
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.7697
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+ - Exact Match: 41.5730
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+ - F1: 1.2761
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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: 2.2261464858561894e-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 OptimizerNames.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: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|
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+ | No log | 1.0 | 6 | 5.7375 | 30.3371 | 2.8248 |
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+ | No log | 2.0 | 12 | 5.2940 | 23.5955 | 3.9492 |
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+ | No log | 3.0 | 18 | 5.0891 | 41.5730 | 0.1310 |
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+ | No log | 4.0 | 24 | 5.0105 | 47.1910 | 0.4682 |
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+ | No log | 5.0 | 30 | 4.7697 | 41.5730 | 1.2761 |
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  ### Framework versions