LABEL_0 LABEL_1 LABEL_2
---
license: mit
tags:
- generated_from_trainer
metrics:
- matthews_correlation
model-index:
- name: TestMeanFraction2
  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. -->

# TestMeanFraction2

This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3967
- Matthews Correlation: 0.2537

## Model description

More information needed

## Intended uses & limitations

"La panique totale" Cette femme trouve une énorme araignée suspendue à sa douche.

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log        | 0.13  | 50   | 1.1126          | 0.1589               |
| No log        | 0.25  | 100  | 1.0540          | 0.1884               |
| No log        | 0.38  | 150  | 1.1533          | 0.0818               |
| No log        | 0.51  | 200  | 1.0676          | 0.1586               |
| No log        | 0.64  | 250  | 0.9949          | 0.2280               |
| No log        | 0.76  | 300  | 1.0343          | 0.2629               |
| No log        | 0.89  | 350  | 1.0203          | 0.2478               |
| No log        | 1.02  | 400  | 1.0041          | 0.2752               |
| No log        | 1.15  | 450  | 1.0808          | 0.2256               |
| 1.023         | 1.27  | 500  | 1.0029          | 0.2532               |
| 1.023         | 1.4   | 550  | 1.0204          | 0.2508               |
| 1.023         | 1.53  | 600  | 1.1377          | 0.1689               |
| 1.023         | 1.65  | 650  | 1.0499          | 0.2926               |
| 1.023         | 1.78  | 700  | 1.0441          | 0.2474               |
| 1.023         | 1.91  | 750  | 1.0279          | 0.2611               |
| 1.023         | 2.04  | 800  | 1.1511          | 0.2804               |
| 1.023         | 2.16  | 850  | 1.2381          | 0.2512               |
| 1.023         | 2.29  | 900  | 1.3340          | 0.2385               |
| 1.023         | 2.42  | 950  | 1.4372          | 0.2842               |
| 0.7325        | 2.54  | 1000 | 1.3967          | 0.2537               |
| 0.7325        | 2.67  | 1050 | 1.4272          | 0.2624               |
| 0.7325        | 2.8   | 1100 | 1.3869          | 0.1941               |
| 0.7325        | 2.93  | 1150 | 1.4983          | 0.2063               |
| 0.7325        | 3.05  | 1200 | 1.4959          | 0.2409               |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0a0+0aef44c
- Datasets 2.0.0
- Tokenizers 0.11.6
