test_trainer
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: 0.7046
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: 8
- eval_batch_size: 8
- 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 |
---|---|---|---|
0.6555 | 0.2 | 500 | 0.5368 |
0.5163 | 0.4 | 1000 | 0.6619 |
0.4749 | 0.6 | 1500 | 0.4899 |
0.4463 | 0.8 | 2000 | 0.4240 |
0.4358 | 1.0 | 2500 | 0.4450 |
0.3586 | 1.2 | 3000 | 0.4560 |
0.3248 | 1.41 | 3500 | 0.5100 |
0.336 | 1.61 | 4000 | 0.5952 |
0.3443 | 1.81 | 4500 | 0.5189 |
0.3075 | 2.01 | 5000 | 0.5482 |
0.2318 | 2.21 | 5500 | 0.7007 |
0.2128 | 2.41 | 6000 | 0.7401 |
0.2168 | 2.61 | 6500 | 0.7252 |
0.2349 | 2.81 | 7000 | 0.7046 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
distilbert/distilbert-base-uncased