bert_tiny_olda_book_5_v1_mnli
This model is a fine-tuned version of gokulsrinivasagan/bert_tiny_olda_book_5_v1 on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.8355
- Accuracy: 0.6236
Model description
More information needed
Intended uses & limitations
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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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.0631 | 1.0 | 1534 | 0.9963 | 0.4937 |
0.9641 | 2.0 | 3068 | 0.9213 | 0.5608 |
0.8975 | 3.0 | 4602 | 0.8754 | 0.5937 |
0.8454 | 4.0 | 6136 | 0.8612 | 0.6062 |
0.8025 | 5.0 | 7670 | 0.8441 | 0.6182 |
0.7639 | 6.0 | 9204 | 0.8546 | 0.6222 |
0.7294 | 7.0 | 10738 | 0.8537 | 0.6231 |
0.6936 | 8.0 | 12272 | 0.8843 | 0.6179 |
0.6619 | 9.0 | 13806 | 0.9189 | 0.6260 |
0.6305 | 10.0 | 15340 | 0.9053 | 0.6291 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1
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Base model
gokulsrinivasagan/bert_tiny_olda_book_5_v1