---
license: mit
tags:
- generated_from_trainer
model-index:
- name: new_camembert_jb
  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. -->

# new_camembert_jb

This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0752
- Overall Precision: 0.8202
- Overall Recall: 0.8595
- Overall F1: 0.8394
- Overall Accuracy: 0.9814
- Er F1: 0.8430
- Oc F1: 0.8418
- Umanprod F1: 0.6933

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Er F1  | Oc F1  | Umanprod F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:------:|:------:|:-----------:|
| 0.2682        | 1.0   | 613  | 0.0813          | 0.7550            | 0.8071         | 0.7802     | 0.9749           | 0.7920 | 0.7709 | 0.6667      |
| 0.0717        | 2.0   | 1226 | 0.0706          | 0.8139            | 0.8411         | 0.8273     | 0.9808           | 0.8446 | 0.8126 | 0.6857      |
| 0.0524        | 3.0   | 1839 | 0.0723          | 0.8215            | 0.8567         | 0.8387     | 0.9812           | 0.8462 | 0.8346 | 0.7368      |
| 0.0372        | 4.0   | 2452 | 0.0752          | 0.8202            | 0.8595         | 0.8394     | 0.9814           | 0.8430 | 0.8418 | 0.6933      |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cpu
- Datasets 2.7.1
- Tokenizers 0.13.2