distilbert-base-uncased-finetuned-pad-clf-v2
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: 0.0935
- Accuracy: 1.0
- F1: 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: 256
- eval_batch_size: 256
- 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 | F1 |
---|---|---|---|---|---|
No log | 1.0 | 4 | 0.6493 | 0.55 | 0.3991 |
No log | 2.0 | 8 | 0.5612 | 0.9083 | 0.9072 |
No log | 3.0 | 12 | 0.4315 | 0.925 | 0.9244 |
0.5882 | 4.0 | 16 | 0.3271 | 0.9667 | 0.9667 |
0.5882 | 5.0 | 20 | 0.2347 | 0.9833 | 0.9833 |
0.5882 | 6.0 | 24 | 0.1715 | 0.9917 | 0.9917 |
0.5882 | 7.0 | 28 | 0.1323 | 0.9917 | 0.9917 |
0.248 | 8.0 | 32 | 0.1093 | 1.0 | 1.0 |
0.248 | 9.0 | 36 | 0.0975 | 1.0 | 1.0 |
0.248 | 10.0 | 40 | 0.0935 | 1.0 | 1.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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