---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
datasets:
- tweet_sentiment_multilingual
metrics:
- accuracy
model-index:
- name: camembert_model
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tweet_sentiment_multilingual
      type: tweet_sentiment_multilingual
      config: french
      split: validation
      args: french
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7654320987654321
---

<!-- 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. -->

# camembert_model

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the tweet_sentiment_multilingual dataset (French portion of it) .
It achieves the following results on the evaluation set:
- Loss: 0.7877
- Accuracy: 0.7654

## Model description

A sentiment Classifier for the french language 
classifies french text to positive, negative or neutral.
## 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: 2e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 115  | 0.8510          | 0.6265   |
| No log        | 2.0   | 230  | 0.7627          | 0.7130   |
| No log        | 3.0   | 345  | 0.6966          | 0.7160   |
| No log        | 4.0   | 460  | 0.6862          | 0.7438   |
| 0.7126        | 5.0   | 575  | 0.6637          | 0.75     |
| 0.7126        | 6.0   | 690  | 0.7121          | 0.7654   |
| 0.7126        | 7.0   | 805  | 0.7641          | 0.7438   |
| 0.7126        | 8.0   | 920  | 0.7662          | 0.7654   |
| 0.2932        | 9.0   | 1035 | 0.7765          | 0.7747   |
| 0.2932        | 10.0  | 1150 | 0.7877          | 0.7654   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0