metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test_trainer
results: []
test_trainer
This model is a fine-tuned version of flaubert/flaubert_small_cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0163
- Accuracy: 0.6225
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 345 | 1.0352 | 0.5435 |
| 1.2697 | 2.0 | 690 | 1.0254 | 0.5696 |
| 1.0075 | 3.0 | 1035 | 1.0079 | 0.5891 |
| 1.0075 | 4.0 | 1380 | 0.9745 | 0.6101 |
| 0.8314 | 5.0 | 1725 | 0.9866 | 0.6188 |
| 0.738 | 6.0 | 2070 | 1.0163 | 0.6225 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3