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xlm-roberta-base-New_VietNam-aug_insert_synonym

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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ThuyNT03 commited on
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Training completed!

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  1. README.md +17 -15
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -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: 1.2506
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- - Accuracy: 0.72
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- - F1: 0.7260
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 8
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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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- | 1.0708 | 1.0 | 86 | 0.8779 | 0.61 | 0.5461 |
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- | 0.8007 | 2.0 | 172 | 0.7836 | 0.66 | 0.6615 |
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- | 0.5802 | 3.0 | 258 | 0.7869 | 0.67 | 0.6704 |
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- | 0.3983 | 4.0 | 344 | 0.8101 | 0.74 | 0.7414 |
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- | 0.259 | 5.0 | 430 | 0.8486 | 0.71 | 0.7175 |
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- | 0.1842 | 6.0 | 516 | 1.1036 | 0.7 | 0.7078 |
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- | 0.1502 | 7.0 | 602 | 1.2329 | 0.7 | 0.7057 |
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- | 0.106 | 8.0 | 688 | 1.2506 | 0.72 | 0.7260 |
 
 
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  ### Framework versions
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  - Transformers 4.32.1
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- - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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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: 1.0069
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+ - Accuracy: 0.69
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+ - F1: 0.7005
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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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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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 | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.0846 | 1.0 | 43 | 0.9691 | 0.59 | 0.4903 |
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+ | 0.8237 | 2.0 | 86 | 0.7961 | 0.64 | 0.6370 |
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+ | 0.6422 | 3.0 | 129 | 0.7569 | 0.71 | 0.7145 |
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+ | 0.515 | 4.0 | 172 | 0.7775 | 0.71 | 0.7151 |
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+ | 0.4099 | 5.0 | 215 | 0.8224 | 0.69 | 0.6970 |
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+ | 0.3239 | 6.0 | 258 | 0.8941 | 0.69 | 0.7013 |
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+ | 0.2709 | 7.0 | 301 | 0.8975 | 0.68 | 0.6907 |
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+ | 0.2011 | 8.0 | 344 | 0.9745 | 0.7 | 0.7120 |
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+ | 0.1795 | 9.0 | 387 | 1.0128 | 0.7 | 0.7120 |
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+ | 0.158 | 10.0 | 430 | 1.0069 | 0.69 | 0.7005 |
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  ### Framework versions
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  - Transformers 4.32.1
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+ - Pytorch 2.0.0
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
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