metadata
base_model: camembert/camembert-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: camembert-large-frenchNER_3entities
results: []
camembert-large-frenchNER_3entities
This model is a fine-tuned version of camembert/camembert-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0846
- Precision: 0.9874
- Recall: 0.9874
- F1: 0.9874
- Accuracy: 0.9874
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0299 | 1.0 | 43650 | 0.0970 | 0.9837 | 0.9837 | 0.9837 | 0.9837 |
| 0.0164 | 2.0 | 87300 | 0.0835 | 0.9864 | 0.9864 | 0.9864 | 0.9864 |
| 0.0108 | 3.0 | 130950 | 0.0846 | 0.9874 | 0.9874 | 0.9874 | 0.9874 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0