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gbert-large-finetuned-cust18
This model is a fine-tuned version of deepset/gbert-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1232
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|
| 0.604 | 1.0 | 391 | 0.3560 |
| 0.3497 | 2.0 | 782 | 0.2838 |
| 0.2812 | 3.0 | 1173 | 0.2484 |
| 0.2452 | 4.0 | 1564 | 0.2232 |
| 0.2253 | 5.0 | 1955 | 0.2240 |
| 0.2202 | 6.0 | 2346 | 0.1993 |
| 0.1922 | 7.0 | 2737 | 0.1747 |
| 0.182 | 8.0 | 3128 | 0.1631 |
| 0.1609 | 9.0 | 3519 | 0.1555 |
| 0.1553 | 10.0 | 3910 | 0.1434 |
| 0.147 | 11.0 | 4301 | 0.1399 |
| 0.144 | 12.0 | 4692 | 0.1340 |
| 0.1307 | 13.0 | 5083 | 0.1319 |
| 0.128 | 14.0 | 5474 | 0.1490 |
| 0.1304 | 15.0 | 5865 | 0.1338 |
| 0.1165 | 16.0 | 6256 | 0.1233 |
| 0.1456 | 17.0 | 6647 | 0.1673 |
| 0.1419 | 18.0 | 7038 | 0.1591 |
| 0.1447 | 19.0 | 7429 | 0.1360 |
| 0.1317 | 20.0 | 7820 | 0.1232 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
