metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-gpqa
results: []
bert-gpqa
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2227
- Accuracy: 0.9174
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: 0.0005
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 28 | 1.3863 | 0.2723 |
| No log | 2.0 | 56 | 1.3860 | 0.3036 |
| No log | 3.0 | 84 | 1.3855 | 0.3125 |
| No log | 4.0 | 112 | 1.3841 | 0.3951 |
| No log | 5.0 | 140 | 1.3562 | 0.5781 |
| No log | 6.0 | 168 | 0.9820 | 0.6674 |
| No log | 7.0 | 196 | 0.6106 | 0.7812 |
| No log | 8.0 | 224 | 0.4142 | 0.8527 |
| No log | 9.0 | 252 | 0.2647 | 0.9241 |
| No log | 10.0 | 280 | 0.2227 | 0.9174 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2