---
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