---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: camembert-ner-finetuned-ner
  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. -->

# camembert-ner-finetuned-ner

This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0862
- Precision: 0.9925
- Recall: 0.9959
- F1: 0.9942
- Accuracy: 0.9896

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1364        | 1.0   | 769  | 0.0832          | 0.9828    | 0.9998 | 0.9912 | 0.9823   |
| 0.0533        | 2.0   | 1538 | 0.0631          | 0.9934    | 0.9923 | 0.9928 | 0.9871   |
| 0.0329        | 3.0   | 2307 | 0.0651          | 0.9912    | 0.9978 | 0.9945 | 0.9897   |
| 0.021         | 4.0   | 3076 | 0.0680          | 0.9937    | 0.9952 | 0.9945 | 0.9899   |
| 0.0171        | 5.0   | 3845 | 0.0628          | 0.9928    | 0.9969 | 0.9948 | 0.9906   |
| 0.0115        | 6.0   | 4614 | 0.0678          | 0.9930    | 0.9963 | 0.9947 | 0.9903   |
| 0.0075        | 7.0   | 5383 | 0.0854          | 0.9928    | 0.9956 | 0.9942 | 0.9896   |
| 0.0045        | 8.0   | 6152 | 0.0862          | 0.9919    | 0.9948 | 0.9934 | 0.9890   |
| 0.0031        | 9.0   | 6921 | 0.0839          | 0.9919    | 0.9958 | 0.9938 | 0.9896   |
| 0.0028        | 10.0  | 7690 | 0.0862          | 0.9925    | 0.9959 | 0.9942 | 0.9896   |


### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1