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recipe-distilbert-upper-Is
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: 0.8565
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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.6309 | 1.0 | 1305 | 1.2607 |
| 1.2639 | 2.0 | 2610 | 1.1291 |
| 1.1592 | 3.0 | 3915 | 1.0605 |
| 1.0987 | 4.0 | 5220 | 1.0128 |
| 1.0569 | 5.0 | 6525 | 0.9796 |
| 1.0262 | 6.0 | 7830 | 0.9592 |
| 1.0032 | 7.0 | 9135 | 0.9352 |
| 0.9815 | 8.0 | 10440 | 0.9186 |
| 0.967 | 9.0 | 11745 | 0.9086 |
| 0.9532 | 10.0 | 13050 | 0.8973 |
| 0.9436 | 11.0 | 14355 | 0.8888 |
| 0.9318 | 12.0 | 15660 | 0.8835 |
| 0.9243 | 13.0 | 16965 | 0.8748 |
| 0.9169 | 14.0 | 18270 | 0.8673 |
| 0.9117 | 15.0 | 19575 | 0.8610 |
| 0.9066 | 16.0 | 20880 | 0.8562 |
| 0.9028 | 17.0 | 22185 | 0.8566 |
| 0.901 | 18.0 | 23490 | 0.8583 |
| 0.8988 | 19.0 | 24795 | 0.8557 |
| 0.8958 | 20.0 | 26100 | 0.8565 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
