my_awesome_model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9309
- Accuracy: 0.63
- F1: 0.6179
- Precision: 0.6132
- Recall: 0.63
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: 16
- eval_batch_size: 16
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.0996 | 1.0 | 22 | 1.0927 | 0.4667 | 0.4068 | 0.4936 | 0.4667 |
| 1.0715 | 2.0 | 44 | 1.0631 | 0.5667 | 0.5266 | 0.4922 | 0.5667 |
| 1.0073 | 3.0 | 66 | 0.9949 | 0.6 | 0.5626 | 0.5997 | 0.6 |
| 0.9014 | 4.0 | 88 | 0.9468 | 0.65 | 0.6234 | 0.6356 | 0.65 |
| 0.8451 | 5.0 | 110 | 0.9229 | 0.6667 | 0.6539 | 0.6571 | 0.6667 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
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