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distilbert_add_pre-training-dim-96
This model is a fine-tuned version of distilbert-base-uncased on the wikitext wikitext-103-raw-v1 dataset. It achieves the following results on the evaluation set:
- Loss: 6.6092
- Accuracy: 0.1494
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 14.685 | 1.0 | 3573 | 9.3922 | 0.1240 |
| 8.0255 | 2.0 | 7146 | 7.1510 | 0.1315 |
| 7.0152 | 3.0 | 10719 | 6.7861 | 0.1482 |
| 6.8127 | 4.0 | 14292 | 6.7053 | 0.1493 |
| 6.74 | 5.0 | 17865 | 6.6695 | 0.1474 |
| 6.7067 | 6.0 | 21438 | 6.6431 | 0.1491 |
| 6.6871 | 7.0 | 25011 | 6.6204 | 0.1483 |
| 6.6748 | 8.0 | 28584 | 6.6250 | 0.1473 |
| 6.6649 | 9.0 | 32157 | 6.6108 | 0.1486 |
| 6.6596 | 10.0 | 35730 | 6.6140 | 0.1497 |
| 6.6536 | 11.0 | 39303 | 6.6067 | 0.1493 |
| 6.6483 | 12.0 | 42876 | 6.6140 | 0.1489 |
| 6.6463 | 13.0 | 46449 | 6.6096 | 0.1484 |
| 6.6434 | 14.0 | 50022 | 6.5570 | 0.1526 |
| 6.6414 | 15.0 | 53595 | 6.5836 | 0.1526 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
