|
|
--- |
|
|
license: mit |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: test_trainer |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# test_trainer |
|
|
|
|
|
This model is a fine-tuned version of [flaubert/flaubert_small_cased](https://huggingface.co/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 |
|
|
|