---
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: XMLRoberta_Dataset59KBoDuoi
  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. -->

# XMLRoberta_Dataset59KBoDuoi

This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4792
- Accuracy: 0.8964
- F1: 0.8969

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.5115  | 200  | 0.4025          | 0.8084   | 0.8111 |
| No log        | 1.0230  | 400  | 0.3500          | 0.8424   | 0.8451 |
| No log        | 1.5345  | 600  | 0.3312          | 0.8637   | 0.8612 |
| 0.4018        | 2.0460  | 800  | 0.3394          | 0.8580   | 0.8610 |
| 0.4018        | 2.5575  | 1000 | 0.2938          | 0.8747   | 0.8760 |
| 0.4018        | 3.0691  | 1200 | 0.2903          | 0.8829   | 0.8841 |
| 0.4018        | 3.5806  | 1400 | 0.2871          | 0.8854   | 0.8859 |
| 0.2576        | 4.0921  | 1600 | 0.2955          | 0.8864   | 0.8873 |
| 0.2576        | 4.6036  | 1800 | 0.2831          | 0.8887   | 0.8894 |
| 0.2576        | 5.1151  | 2000 | 0.2952          | 0.8885   | 0.8898 |
| 0.2576        | 5.6266  | 2200 | 0.2947          | 0.8872   | 0.8881 |
| 0.2036        | 6.1381  | 2400 | 0.3086          | 0.8887   | 0.8902 |
| 0.2036        | 6.6496  | 2600 | 0.2939          | 0.8924   | 0.8931 |
| 0.2036        | 7.1611  | 2800 | 0.3368          | 0.8879   | 0.8895 |
| 0.2036        | 7.6726  | 3000 | 0.3162          | 0.8924   | 0.8932 |
| 0.1616        | 8.1841  | 3200 | 0.3423          | 0.8909   | 0.8919 |
| 0.1616        | 8.6957  | 3400 | 0.3475          | 0.8940   | 0.8945 |
| 0.1616        | 9.2072  | 3600 | 0.3546          | 0.8914   | 0.8923 |
| 0.1616        | 9.7187  | 3800 | 0.3505          | 0.8941   | 0.8947 |
| 0.1291        | 10.2302 | 4000 | 0.3850          | 0.8934   | 0.8941 |
| 0.1291        | 10.7417 | 4200 | 0.3718          | 0.8957   | 0.8963 |
| 0.1291        | 11.2532 | 4400 | 0.3893          | 0.8916   | 0.8924 |
| 0.1291        | 11.7647 | 4600 | 0.3923          | 0.8949   | 0.8955 |
| 0.1047        | 12.2762 | 4800 | 0.4213          | 0.8959   | 0.8968 |
| 0.1047        | 12.7877 | 5000 | 0.3877          | 0.8951   | 0.8961 |
| 0.1047        | 13.2992 | 5200 | 0.3972          | 0.8990   | 0.8992 |
| 0.1047        | 13.8107 | 5400 | 0.3896          | 0.8928   | 0.8937 |
| 0.0865        | 14.3223 | 5600 | 0.4290          | 0.8961   | 0.8964 |
| 0.0865        | 14.8338 | 5800 | 0.4360          | 0.8977   | 0.8979 |
| 0.0865        | 15.3453 | 6000 | 0.4398          | 0.8958   | 0.8963 |
| 0.0865        | 15.8568 | 6200 | 0.4357          | 0.8951   | 0.8955 |
| 0.0726        | 16.3683 | 6400 | 0.4662          | 0.8952   | 0.8953 |
| 0.0726        | 16.8798 | 6600 | 0.4608          | 0.8945   | 0.8955 |
| 0.0726        | 17.3913 | 6800 | 0.4714          | 0.8952   | 0.8954 |
| 0.0726        | 17.9028 | 7000 | 0.4638          | 0.8967   | 0.8971 |
| 0.0612        | 18.4143 | 7200 | 0.4783          | 0.8969   | 0.8971 |
| 0.0612        | 18.9258 | 7400 | 0.4856          | 0.8962   | 0.8967 |
| 0.0612        | 19.4373 | 7600 | 0.4779          | 0.8958   | 0.8963 |
| 0.0612        | 19.9488 | 7800 | 0.4792          | 0.8964   | 0.8969 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1