pretrain_model
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6196
- Precision: 0.6607
- Recall: 0.6589
- F1: 0.6598
- Accuracy: 0.6575
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.6965 | 0.1377 | 500 | 0.6910 | 0.526 | 1.0 | 0.6894 | 0.526 |
0.6963 | 0.2755 | 1000 | 0.6921 | 0.526 | 1.0 | 0.6894 | 0.526 |
0.6957 | 0.4132 | 1500 | 0.6666 | 0.6154 | 0.7300 | 0.6678 | 0.618 |
0.6914 | 0.5510 | 2000 | 0.6834 | 0.7069 | 0.4677 | 0.5629 | 0.618 |
0.6768 | 0.6887 | 2500 | 0.6838 | 0.6412 | 0.6388 | 0.64 | 0.622 |
0.6786 | 0.8264 | 3000 | 0.6539 | 0.7273 | 0.4259 | 0.5372 | 0.614 |
0.663 | 0.9642 | 3500 | 0.6743 | 0.6560 | 0.5437 | 0.5946 | 0.61 |
0.6564 | 1.1019 | 4000 | 0.6381 | 0.6763 | 0.6198 | 0.6468 | 0.644 |
0.6468 | 1.2397 | 4500 | 0.6010 | 0.6613 | 0.7871 | 0.7188 | 0.676 |
0.6275 | 1.3774 | 5000 | 0.6103 | 0.7246 | 0.5703 | 0.6383 | 0.66 |
0.6275 | 1.5152 | 5500 | 0.6018 | 0.7311 | 0.5894 | 0.6526 | 0.67 |
0.6141 | 1.6529 | 6000 | 0.5947 | 0.7269 | 0.6578 | 0.6906 | 0.69 |
0.617 | 1.7906 | 6500 | 0.5872 | 0.7165 | 0.6920 | 0.7041 | 0.694 |
0.6059 | 1.9284 | 7000 | 0.5816 | 0.7227 | 0.7034 | 0.7129 | 0.702 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
FacebookAI/roberta-base