---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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: 0.0970
- Precision: 0.9848
- Recall: 0.9848
- F1: 0.9848
- Accuracy: 0.9848

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0349        | 1.0   | 43650  | 0.0952          | 0.9822    | 0.9822 | 0.9822 | 0.9822   |
| 0.0194        | 2.0   | 87300  | 0.0942          | 0.9840    | 0.9840 | 0.9840 | 0.9840   |
| 0.0111        | 3.0   | 130950 | 0.0970          | 0.9848    | 0.9848 | 0.9848 | 0.9848   |


### Framework versions

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