metadata
library_name: transformers
license: mit
base_model: almanach/camembertav2-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: camembertav2-base-frenchNER_3entities
results: []
camembertav2-base-frenchNER_3entities
This model is a fine-tuned version of almanach/camembertav2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0880
- Precision: 0.9859
- Recall: 0.9859
- F1: 0.9859
- Accuracy: 0.9859
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0335 | 1.0 | 43650 | 0.0854 | 0.9833 | 0.9833 | 0.9833 | 0.9833 |
| 0.0169 | 2.0 | 87300 | 0.0821 | 0.9854 | 0.9854 | 0.9854 | 0.9854 |
| 0.0103 | 3.0 | 130950 | 0.0880 | 0.9859 | 0.9859 | 0.9859 | 0.9859 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1