results
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2696
- Accuracy: 0.92
- Precision: 0.9170
- Recall: 0.9236
- F1: 0.9203
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: 16
- eval_batch_size: 16
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2796 | 1.0 | 2500 | 0.2519 | 0.907 | 0.9299 | 0.8804 | 0.9045 |
| 0.1406 | 2.0 | 5000 | 0.2696 | 0.92 | 0.9170 | 0.9236 | 0.9203 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for arashghsz/my-finetuned-model
Base model
distilbert/distilbert-base-uncased