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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: 0.7335
- Accuracy: 0.6760
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.56 | 100 | 0.6407 | 0.6251 |
No log | 1.12 | 200 | 0.7067 | 0.6953 |
No log | 1.68 | 300 | 0.6478 | 0.6796 |
No log | 2.23 | 400 | 0.7657 | 0.6901 |
0.4528 | 2.79 | 500 | 0.8630 | 0.6733 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
distilbert/distilbert-base-uncased