---
library_name: transformers
license: mit
base_model: almanach/camembert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_model
  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. -->

# my_awesome_wnut_model

This model is a fine-tuned version of [almanach/camembert-base](https://huggingface.co/almanach/camembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0159
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9970

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 160  | 0.1652          | 0.0       | 0.0    | 0.0 | 0.9528   |
| No log        | 2.0   | 320  | 0.0499          | 0.0       | 0.0    | 0.0 | 0.9943   |
| No log        | 3.0   | 480  | 0.0303          | 0.0       | 0.0    | 0.0 | 0.9960   |
| 0.1412        | 4.0   | 640  | 0.0239          | 0.0       | 0.0    | 0.0 | 0.9967   |
| 0.1412        | 5.0   | 800  | 0.0206          | 0.0       | 0.0    | 0.0 | 0.9968   |
| 0.1412        | 6.0   | 960  | 0.0186          | 0.0       | 0.0    | 0.0 | 0.9969   |
| 0.0254        | 7.0   | 1120 | 0.0173          | 0.0       | 0.0    | 0.0 | 0.9970   |
| 0.0254        | 8.0   | 1280 | 0.0165          | 0.0       | 0.0    | 0.0 | 0.9970   |
| 0.0254        | 9.0   | 1440 | 0.0161          | 0.0       | 0.0    | 0.0 | 0.9970   |
| 0.0184        | 10.0  | 1600 | 0.0159          | 0.0       | 0.0    | 0.0 | 0.9970   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3