category-1-balanced-distilbert-base-uncased-v4
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0153
- Accuracy: 0.7027
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: 45
- eval_batch_size: 45
- 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 | 496 | 1.1978 | 0.6253 |
1.3354 | 2.0 | 992 | 1.0061 | 0.6636 |
0.8357 | 3.0 | 1488 | 0.9692 | 0.6828 |
0.6973 | 4.0 | 1984 | 0.9139 | 0.7015 |
0.5999 | 5.0 | 2480 | 0.9239 | 0.7017 |
0.5091 | 6.0 | 2976 | 0.9668 | 0.6951 |
0.447 | 7.0 | 3472 | 0.9880 | 0.6997 |
0.3884 | 8.0 | 3968 | 0.9850 | 0.7048 |
0.342 | 9.0 | 4464 | 1.0228 | 0.6979 |
0.3136 | 10.0 | 4960 | 1.0153 | 0.7027 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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