Edit model card

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
Downloads last month
208
Safetensors
Model size
111M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for ac0hik/Sentiment_Analysis_French

Finetuned
(92)
this model

Space using ac0hik/Sentiment_Analysis_French 1

Evaluation results