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distilbert-base-uncased_fold_3_binary_v1
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: 1.9405
- F1: 0.7878
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: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 289 | 0.4630 | 0.7897 |
| 0.3954 | 2.0 | 578 | 0.4549 | 0.7936 |
| 0.3954 | 3.0 | 867 | 0.6527 | 0.7868 |
| 0.1991 | 4.0 | 1156 | 0.7510 | 0.7951 |
| 0.1991 | 5.0 | 1445 | 0.9327 | 0.8000 |
| 0.095 | 6.0 | 1734 | 1.0974 | 0.7859 |
| 0.0347 | 7.0 | 2023 | 1.2692 | 0.7919 |
| 0.0347 | 8.0 | 2312 | 1.3718 | 0.7921 |
| 0.0105 | 9.0 | 2601 | 1.4679 | 0.7999 |
| 0.0105 | 10.0 | 2890 | 1.5033 | 0.8070 |
| 0.0079 | 11.0 | 3179 | 1.6074 | 0.8008 |
| 0.0079 | 12.0 | 3468 | 1.6921 | 0.7904 |
| 0.0053 | 13.0 | 3757 | 1.7079 | 0.7945 |
| 0.0054 | 14.0 | 4046 | 1.8361 | 0.7887 |
| 0.0054 | 15.0 | 4335 | 1.7695 | 0.7873 |
| 0.0046 | 16.0 | 4624 | 1.7934 | 0.7917 |
| 0.0046 | 17.0 | 4913 | 1.8036 | 0.8008 |
| 0.0064 | 18.0 | 5202 | 1.8780 | 0.7888 |
| 0.0064 | 19.0 | 5491 | 1.8943 | 0.7923 |
| 0.0032 | 20.0 | 5780 | 1.8694 | 0.7905 |
| 0.002 | 21.0 | 6069 | 1.9348 | 0.7869 |
| 0.002 | 22.0 | 6358 | 1.9578 | 0.7804 |
| 0.0036 | 23.0 | 6647 | 1.9438 | 0.7827 |
| 0.0036 | 24.0 | 6936 | 1.9386 | 0.7878 |
| 0.0011 | 25.0 | 7225 | 1.9405 | 0.7878 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
