This model is a fine-tuned version of camembert-base on the French subset of the tweet_sentiment_multilingual dataset, augmented with additional curated sentiment data from various sources. . 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

ac0hik/Sentiment_Analysis_French

camembert_model