SAE-distilbert-base-uncased
This model is a fine-tuned version of distilbert-base-uncased on the jgammack/SAE-door-abstracts dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2970
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 15
- eval_batch_size: 15
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5323 | 1.0 | 37 | 2.4503 |
| 2.4968 | 2.0 | 74 | 2.4571 |
| 2.4688 | 3.0 | 111 | 2.4099 |
| 2.419 | 4.0 | 148 | 2.3343 |
| 2.4229 | 5.0 | 185 | 2.3072 |
| 2.4067 | 6.0 | 222 | 2.2927 |
| 2.3877 | 7.0 | 259 | 2.2836 |
| 2.374 | 8.0 | 296 | 2.3767 |
| 2.3582 | 9.0 | 333 | 2.2493 |
| 2.356 | 10.0 | 370 | 2.2847 |
| 2.3294 | 11.0 | 407 | 2.3234 |
| 2.3358 | 12.0 | 444 | 2.2660 |
| 2.3414 | 13.0 | 481 | 2.2887 |
| 2.3154 | 14.0 | 518 | 2.3737 |
| 2.311 | 15.0 | 555 | 2.2686 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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