distilbert-base-uncased-finetuned-squad
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.4253
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.635 | 1.0 | 1384 | 4.5790 |
| 4.4544 | 2.0 | 2768 | 4.4523 |
| 4.2617 | 3.0 | 4152 | 4.3310 |
| 4.1031 | 4.0 | 5536 | 4.2816 |
| 3.9956 | 5.0 | 6920 | 4.2679 |
| 3.8676 | 6.0 | 8304 | 4.2379 |
| 3.7723 | 7.0 | 9688 | 4.3650 |
| 3.6775 | 8.0 | 11072 | 4.2837 |
| 3.5571 | 9.0 | 12456 | 4.3691 |
| 3.469 | 10.0 | 13840 | 4.3981 |
| 3.3777 | 11.0 | 15224 | 4.4369 |
| 3.2817 | 12.0 | 16608 | 4.5183 |
| 3.1812 | 13.0 | 17992 | 4.6001 |
| 3.0944 | 14.0 | 19376 | 4.6602 |
| 3.0193 | 15.0 | 20760 | 4.7157 |
| 2.9398 | 16.0 | 22144 | 4.7307 |
| 2.8544 | 17.0 | 23528 | 4.8100 |
| 2.7735 | 18.0 | 24912 | 4.9065 |
| 2.7244 | 19.0 | 26296 | 4.9776 |
| 2.6561 | 20.0 | 27680 | 5.0650 |
| 2.5995 | 21.0 | 29064 | 5.1428 |
| 2.5324 | 22.0 | 30448 | 5.1684 |
| 2.4836 | 23.0 | 31832 | 5.1686 |
| 2.4398 | 24.0 | 33216 | 5.2283 |
| 2.4037 | 25.0 | 34600 | 5.2688 |
| 2.3645 | 26.0 | 35984 | 5.3086 |
| 2.3382 | 27.0 | 37368 | 5.3551 |
| 2.3117 | 28.0 | 38752 | 5.4321 |
| 2.2725 | 29.0 | 40136 | 5.4103 |
| 2.2693 | 30.0 | 41520 | 5.4253 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for toorgil/distilbert-base-uncased-finetuned-squad
Base model
distilbert/distilbert-base-uncased