my_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: 0.4081
- Accuracy: 0.88
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 | 125 | 0.5176 | 0.85 |
No log | 2.0 | 250 | 0.3960 | 0.88 |
No log | 3.0 | 375 | 0.3505 | 0.888 |
0.4861 | 4.0 | 500 | 0.3506 | 0.89 |
0.4861 | 5.0 | 625 | 0.3605 | 0.89 |
0.4861 | 6.0 | 750 | 0.3556 | 0.89 |
0.4861 | 7.0 | 875 | 0.4019 | 0.882 |
0.1193 | 8.0 | 1000 | 0.4135 | 0.88 |
0.1193 | 9.0 | 1125 | 0.4071 | 0.882 |
0.1193 | 10.0 | 1250 | 0.4081 | 0.88 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Base model
distilbert/distilbert-base-uncased