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Token Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
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  1. README.md +20 -15
  2. model.safetensors +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ 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: 0.1050
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  - Accuracy: 0.9702
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- - Precision: 0.6561
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- - Recall: 0.6741
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- - F1: 0.6650
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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 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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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 1.0 | 51 | 0.1397 | 0.9582 | 0.7697 | 0.4954 | 0.6028 |
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- | No log | 2.0 | 102 | 0.1134 | 0.9671 | 0.6508 | 0.6244 | 0.6373 |
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- | No log | 3.0 | 153 | 0.1069 | 0.9696 | 0.6804 | 0.6223 | 0.6501 |
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- | No log | 4.0 | 204 | 0.1059 | 0.9694 | 0.6334 | 0.6822 | 0.6569 |
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- | No log | 5.0 | 255 | 0.1050 | 0.9702 | 0.6561 | 0.6741 | 0.6650 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.52.4
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  - Pytorch 2.7.1+cu126
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- - Datasets 4.0.0
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- - Tokenizers 0.21.1
 
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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: 0.1043
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  - Accuracy: 0.9702
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+ - Precision: 0.6321
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+ - Recall: 0.6680
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+ - F1: 0.6496
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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 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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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 26 | 0.1939 | 0.9458 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 52 | 0.1404 | 0.9584 | 0.6675 | 0.5381 | 0.5958 |
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+ | No log | 3.0 | 78 | 0.1218 | 0.9643 | 0.6287 | 0.6102 | 0.6193 |
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+ | No log | 4.0 | 104 | 0.1090 | 0.9672 | 0.6127 | 0.6487 | 0.6302 |
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+ | No log | 5.0 | 130 | 0.1049 | 0.9690 | 0.6384 | 0.6274 | 0.6329 |
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+ | No log | 6.0 | 156 | 0.1013 | 0.9687 | 0.6169 | 0.6081 | 0.6125 |
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+ | No log | 7.0 | 182 | 0.1030 | 0.9691 | 0.5997 | 0.6964 | 0.6444 |
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+ | No log | 8.0 | 208 | 0.1067 | 0.9679 | 0.5779 | 0.7340 | 0.6467 |
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+ | No log | 9.0 | 234 | 0.1058 | 0.9697 | 0.6498 | 0.6142 | 0.6315 |
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+ | No log | 10.0 | 260 | 0.1043 | 0.9702 | 0.6321 | 0.6680 | 0.6496 |
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  ### Framework versions
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+ - Transformers 4.53.1
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  - Pytorch 2.7.1+cu126
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.2
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