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dbert-finetuned-433-1
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5437
- Accuracy: 0.8438
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: 32
- eval_batch_size: 32
- 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 |
---|---|---|---|---|
0.3563 | 1.0 | 6250 | 0.3636 | 0.8400 |
0.2989 | 2.0 | 12500 | 0.3517 | 0.8490 |
0.2287 | 3.0 | 18750 | 0.3928 | 0.8486 |
0.1646 | 4.0 | 25000 | 0.4724 | 0.8458 |
0.1383 | 5.0 | 31250 | 0.5437 | 0.8438 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3