bert-base-uncased-finetuned-mnli
This model is a fine-tuned version of bert-base-uncased on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.5723
- Accuracy: 0.8464
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 0.5193 | 1.0 | 24544 | 0.8373 | 0.4271 |
| 0.3333 | 2.0 | 49088 | 0.8451 | 0.4371 |
| 0.2214 | 3.0 | 73632 | 0.8469 | 0.5565 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Model tree for w05230505/bert-base-uncased-finetuned-mnli
Base model
google-bert/bert-base-uncased