---
base_model: camembert/camembert-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: relatives_psr_seq-cbert_finetuned
  results: []
datasets:
- djamina/relatives_psr
language:
- fr
pipeline_tag: token-classification
---

<!-- 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. -->

# relatives_psr_seq-cbert_finetuned

This model is a fine-tuned version of [camembert/camembert-large](https://huggingface.co/camembert/camembert-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7099
- Precision: 0.6914
- Recall: 0.2252
- F1: 0.2193
- Accuracy: 0.7578

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 49   | 0.8241          | 0.9512    | 0.2    | 0.1722 | 0.7560   |
| No log        | 2.0   | 98   | 0.8026          | 0.8243    | 0.2100 | 0.1933 | 0.7555   |
| No log        | 3.0   | 147  | 0.7535          | 0.8077    | 0.2045 | 0.1823 | 0.7563   |
| No log        | 4.0   | 196  | 0.7228          | 0.8227    | 0.2220 | 0.2109 | 0.7586   |
| No log        | 5.0   | 245  | 0.7099          | 0.6914    | 0.2252 | 0.2193 | 0.7578   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1