bert-large-cased-lora-1.58M-snli-model2
This model is a fine-tuned version of bert-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8331
- Accuracy: 0.687
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: 256
- eval_batch_size: 256
- seed: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5164 | 1.0 | 2146 | 0.4262 | 0.8406 |
| 0.4687 | 2.0 | 4292 | 0.3904 | 0.8540 |
| 0.4562 | 3.0 | 6438 | 0.3824 | 0.8575 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for varun-v-rao/bert-large-cased-lora-1.58M-snli-model2
Base model
google-bert/bert-large-cased