working
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: 0.0002
- Accuracy: 1.0
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 80 | 0.0041 | 1.0 |
No log | 2.0 | 160 | 0.0012 | 1.0 |
No log | 3.0 | 240 | 0.0007 | 1.0 |
No log | 4.0 | 320 | 0.0004 | 1.0 |
No log | 5.0 | 400 | 0.0003 | 1.0 |
No log | 6.0 | 480 | 0.0002 | 1.0 |
0.0303 | 7.0 | 560 | 0.0002 | 1.0 |
0.0303 | 8.0 | 640 | 0.0002 | 1.0 |
0.0303 | 9.0 | 720 | 0.0002 | 1.0 |
0.0303 | 10.0 | 800 | 0.0002 | 1.0 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for briangilbert/working
Base model
distilbert/distilbert-base-uncased