distilbert_pork_classifier
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: 0.0066
- F1: 0.9667
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: 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 | F1 |
---|---|---|---|---|
0.0406 | 1.0 | 760 | 0.0126 | 0.8727 |
0.0083 | 2.0 | 1520 | 0.0061 | 0.9667 |
0.0017 | 3.0 | 2280 | 0.0061 | 0.9667 |
0.0005 | 4.0 | 3040 | 0.0064 | 0.9667 |
0.0001 | 5.0 | 3800 | 0.0066 | 0.9667 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu116
- Datasets 2.19.0
- Tokenizers 0.13.3
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