metadata
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
camembert_model
This model is a fine-tuned version of 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