MTL-bert-base-uncased
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9283
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: 7
- eval_batch_size: 7
- 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 |
---|---|---|---|
2.4409 | 1.0 | 99 | 2.1982 |
2.2905 | 2.0 | 198 | 2.1643 |
2.1974 | 3.0 | 297 | 2.1168 |
2.15 | 4.0 | 396 | 2.0023 |
2.0823 | 5.0 | 495 | 2.0199 |
2.0752 | 6.0 | 594 | 1.9061 |
2.0408 | 7.0 | 693 | 1.9770 |
1.9984 | 8.0 | 792 | 1.9322 |
1.9933 | 9.0 | 891 | 1.9167 |
1.9806 | 10.0 | 990 | 1.9652 |
1.9436 | 11.0 | 1089 | 1.9308 |
1.9491 | 12.0 | 1188 | 1.9064 |
1.929 | 13.0 | 1287 | 1.8831 |
1.9096 | 14.0 | 1386 | 1.8927 |
1.9032 | 15.0 | 1485 | 1.9117 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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