---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm_roberta_45k_boduoi_test10k
  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_45k_boduoi_test10k

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3960
- Accuracy: 0.8843
- F1: 0.8845

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.4685        | 1.0   | 1407  | 0.3630          | 0.8416   | 0.8371 |
| 0.3354        | 2.0   | 2814  | 0.3028          | 0.8692   | 0.8708 |
| 0.2853        | 3.0   | 4221  | 0.2972          | 0.8797   | 0.8803 |
| 0.2456        | 4.0   | 5628  | 0.2981          | 0.8816   | 0.8822 |
| 0.2166        | 5.0   | 7035  | 0.3029          | 0.8816   | 0.8824 |
| 0.1854        | 6.0   | 8442  | 0.3522          | 0.8842   | 0.8848 |
| 0.1618        | 7.0   | 9849  | 0.3546          | 0.8853   | 0.8856 |
| 0.1447        | 8.0   | 11256 | 0.3729          | 0.8844   | 0.8847 |
| 0.1343        | 9.0   | 12663 | 0.3904          | 0.8836   | 0.8838 |
| 0.1283        | 10.0  | 14070 | 0.3960          | 0.8843   | 0.8845 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1