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bert-tomi
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: 0.4198
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 20 | 1.5815 |
| No log | 2.0 | 40 | 0.7518 |
| No log | 3.0 | 60 | 0.7153 |
| No log | 4.0 | 80 | 0.6354 |
| No log | 5.0 | 100 | 0.5895 |
| No log | 6.0 | 120 | 0.4882 |
| No log | 7.0 | 140 | 0.4590 |
| No log | 8.0 | 160 | 0.4303 |
| No log | 9.0 | 180 | 0.4644 |
| No log | 10.0 | 200 | 0.4416 |
| No log | 11.0 | 220 | 0.4348 |
| No log | 12.0 | 240 | 0.5306 |
| No log | 13.0 | 260 | 0.4412 |
| No log | 14.0 | 280 | 0.4053 |
| No log | 15.0 | 300 | 0.4185 |
| No log | 16.0 | 320 | 0.3982 |
| No log | 17.0 | 340 | 0.4291 |
| No log | 18.0 | 360 | 0.4316 |
| No log | 19.0 | 380 | 0.4328 |
| No log | 20.0 | 400 | 0.4198 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.10.1
- Tokenizers 0.12.1
