distilbert-base-uncased-finetuned-classification
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: 0.1988
- Accuracy: 0.0003
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.4521 | 1.0 | 938 | 0.6710 | 0.0 |
| 0.3656 | 2.0 | 1876 | 0.2271 | 0.0 |
| 0.0669 | 3.0 | 2814 | 0.1934 | 0.0 |
| 0.0288 | 4.0 | 3752 | 0.1963 | 0.0 |
| 0.0134 | 5.0 | 4690 | 0.1922 | 0.0 |
| 0.0091 | 6.0 | 5628 | 0.1988 | 0.0003 |
| 0.006 | 7.0 | 6566 | 0.1982 | 0.0003 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for piecake/distilbert-base-uncased-finetuned-classification
Base model
distilbert/distilbert-base-uncased