metadata
library_name: transformers
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-model-camembert
results: []
ner-model-camembert
This model is a fine-tuned version of camembert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3660
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8739
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: 16
- eval_batch_size: 16
- 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 24 | 0.3795 | 0.0 | 0.0 | 0.0 | 0.8739 |
| No log | 2.0 | 48 | 0.3660 | 0.0 | 0.0 | 0.0 | 0.8739 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0