category-1-9-categories-distilbert-base-uncased-v1
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: 0.7365
- Accuracy: 0.7541
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7339 | 1.0 | 2000 | 0.8391 | 0.7079 |
0.6192 | 2.0 | 4000 | 0.7575 | 0.7415 |
0.5365 | 3.0 | 6000 | 0.7113 | 0.7524 |
0.4686 | 4.0 | 8000 | 0.7426 | 0.7477 |
0.4164 | 5.0 | 10000 | 0.7365 | 0.7541 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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