results
This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6240
- Accuracy: 0.7872
- F1: 0.7875
- Precision: 0.7879
- Recall: 0.7872
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6345 | 0.7599 | 500 | 0.6403 | 0.7393 | 0.7413 | 0.7480 | 0.7393 |
| 0.4407 | 1.5198 | 1000 | 0.5656 | 0.7723 | 0.7727 | 0.7747 | 0.7723 |
| 0.2476 | 2.2796 | 1500 | 0.6295 | 0.7841 | 0.7843 | 0.7845 | 0.7841 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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