metadata

license: mit
base_model: almanach/camembert-base
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: camenBERT
    results: []

camenBERT

This model is a fine-tuned version of almanach/camembert-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5023
Precision: 0.9645
Recall: 0.9718
F1: 0.9681
Accuracy: 0.9709

Model description

More information needed

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: 10
eval_batch_size: 10
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.6427	1.0	1782	0.5023	0.9645	0.9718	0.9681	0.9709

Framework versions

Transformers 4.40.0
Pytorch 2.2.2+cu121
Datasets 2.19.0
Tokenizers 0.19.1