---
library_name: transformers
license: mit
base_model: almanach/camembertv2-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: camembertv2-base-frenchNER_3entities
  results: []
---

```
{'LOC': {'precision': 0.9510338498083464,
  'recall': 0.9654366094263792,
  'f1': 0.9581811094289677,
  'number': 54740},
 'MISC': {'precision': 0.8600569108290437,
  'recall': 0.7587510224804671,
  'f1': 0.806234077626255,
  'number': 35453},
 'O': {'precision': 0.9909218534126304,
  'recall': 0.9936490359966582,
  'f1': 0.9922835708676133,
  'number': 805547},
 'ORG': {'precision': 0.8822008564272441,
  'recall': 0.921045972163644,
  'f1': 0.901205018157808,
  'number': 11855},
 'PER': {'precision': 0.973038794785731,
  'recall': 0.9823632323041278,
  'f1': 0.9776787815093096,
  'number': 63447},
 'overall_precision': 0.9818586631680195,
 'overall_recall': 0.9818586631680195,
 'overall_f1': 0.9818586631680195,
 'overall_accuracy': 0.9818586631680195}
```

# camembertv2-base-frenchNER_3entities

This model is a fine-tuned version of [almanach/camembertv2-base](https://huggingface.co/almanach/camembertv2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0621
- Precision: 0.9822
- Recall: 0.9822
- F1: 0.9822
- Accuracy: 0.9822

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0438        | 1.0   | 41095  | 0.0620          | 0.9801    | 0.9801 | 0.9801 | 0.9801   |
| 0.0331        | 2.0   | 82190  | 0.0581          | 0.9816    | 0.9816 | 0.9816 | 0.9816   |
| 0.0176        | 3.0   | 123285 | 0.0621          | 0.9822    | 0.9822 | 0.9822 | 0.9822   |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1