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my_awesome_model
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: 0.3807
- Accuracy: 0.9048
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 11 | 1.0310 | 0.8333 |
| No log | 2.0 | 22 | 0.7747 | 0.8571 |
| No log | 3.0 | 33 | 0.6065 | 0.8333 |
| No log | 4.0 | 44 | 0.4970 | 0.8571 |
| No log | 5.0 | 55 | 0.4455 | 0.8810 |
| No log | 6.0 | 66 | 0.4230 | 0.9048 |
| No log | 7.0 | 77 | 0.4064 | 0.9048 |
| No log | 8.0 | 88 | 0.3917 | 0.9048 |
| No log | 9.0 | 99 | 0.3832 | 0.9048 |
| No log | 10.0 | 110 | 0.3807 | 0.9048 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
