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distilbert-base-uncased_fold_8_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: 1.6283
- F1: 0.8178
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 | 290 | 0.4038 | 0.7981 |
| 0.409 | 2.0 | 580 | 0.4023 | 0.8176 |
| 0.409 | 3.0 | 870 | 0.5245 | 0.8169 |
| 0.1938 | 4.0 | 1160 | 0.6242 | 0.8298 |
| 0.1938 | 5.0 | 1450 | 0.8432 | 0.8159 |
| 0.0848 | 6.0 | 1740 | 1.0887 | 0.8015 |
| 0.038 | 7.0 | 2030 | 1.0700 | 0.8167 |
| 0.038 | 8.0 | 2320 | 1.0970 | 0.8241 |
| 0.0159 | 9.0 | 2610 | 1.2474 | 0.8142 |
| 0.0159 | 10.0 | 2900 | 1.3453 | 0.8184 |
| 0.01 | 11.0 | 3190 | 1.4412 | 0.8147 |
| 0.01 | 12.0 | 3480 | 1.4263 | 0.8181 |
| 0.007 | 13.0 | 3770 | 1.3859 | 0.8258 |
| 0.0092 | 14.0 | 4060 | 1.4633 | 0.8128 |
| 0.0092 | 15.0 | 4350 | 1.4304 | 0.8206 |
| 0.0096 | 16.0 | 4640 | 1.5081 | 0.8149 |
| 0.0096 | 17.0 | 4930 | 1.5239 | 0.8189 |
| 0.0047 | 18.0 | 5220 | 1.5268 | 0.8151 |
| 0.0053 | 19.0 | 5510 | 1.5445 | 0.8173 |
| 0.0053 | 20.0 | 5800 | 1.6051 | 0.8180 |
| 0.0014 | 21.0 | 6090 | 1.5981 | 0.8211 |
| 0.0014 | 22.0 | 6380 | 1.5957 | 0.8225 |
| 0.001 | 23.0 | 6670 | 1.5838 | 0.8189 |
| 0.001 | 24.0 | 6960 | 1.6301 | 0.8178 |
| 0.0018 | 25.0 | 7250 | 1.6283 | 0.8178 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
