crypto_fundamental_news_text_classifier-distilbert-base-uncased
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3716
- Accuracy: 0.9194
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: 1e-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
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0913 | 1.0 | 8 | 1.1070 | 0.2097 |
| 1.0507 | 2.0 | 16 | 1.0611 | 0.4032 |
| 0.9942 | 3.0 | 24 | 0.9997 | 0.5161 |
| 0.8923 | 4.0 | 32 | 0.9018 | 0.5968 |
| 0.7789 | 5.0 | 40 | 0.8149 | 0.6774 |
| 0.675 | 6.0 | 48 | 0.7557 | 0.7903 |
| 0.6047 | 7.0 | 56 | 0.6935 | 0.7903 |
| 0.5335 | 8.0 | 64 | 0.6468 | 0.8548 |
| 0.4758 | 9.0 | 72 | 0.6036 | 0.8871 |
| 0.43 | 10.0 | 80 | 0.5686 | 0.8871 |
| 0.3939 | 11.0 | 88 | 0.5312 | 0.9032 |
| 0.349 | 12.0 | 96 | 0.4888 | 0.9194 |
| 0.3127 | 13.0 | 104 | 0.4539 | 0.9194 |
| 0.2806 | 14.0 | 112 | 0.4281 | 0.9194 |
| 0.2624 | 15.0 | 120 | 0.4062 | 0.9194 |
| 0.2362 | 16.0 | 128 | 0.3953 | 0.9194 |
| 0.2231 | 17.0 | 136 | 0.3839 | 0.9194 |
| 0.2161 | 18.0 | 144 | 0.3799 | 0.9194 |
| 0.2023 | 19.0 | 152 | 0.3753 | 0.9194 |
| 0.1982 | 20.0 | 160 | 0.3716 | 0.9194 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.0