README.md

---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: xlm-roberta-base_single_finetuned_on_cedr_augmented
  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. -->

# xlm-roberta-base_single_finetuned_on_cedr_augmented

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4650
- Accuracy: 0.8820
- F1: 0.8814
- Precision: 0.8871
- Recall: 0.8820

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8868        | 1.0   | 69   | 0.4939          | 0.8403   | 0.8376 | 0.8431    | 0.8403 |
| 0.4248        | 2.0   | 138  | 0.3969          | 0.8779   | 0.8768 | 0.8798    | 0.8779 |
| 0.3197        | 3.0   | 207  | 0.4019          | 0.8758   | 0.8757 | 0.8758    | 0.8758 |
| 0.2737        | 4.0   | 276  | 0.3915          | 0.8831   | 0.8827 | 0.8847    | 0.8831 |
| 0.2053        | 5.0   | 345  | 0.4445          | 0.8643   | 0.8650 | 0.8714    | 0.8643 |
| 0.1705        | 6.0   | 414  | 0.4650          | 0.8820   | 0.8814 | 0.8871    | 0.8820 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1