---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-roberta-base-Mixed-delete
  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-Mixed-delete

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6994
- Accuracy: 0.7852
- F1: 0.7857

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.221         | 1.0   | 321  | 1.0439          | 0.7897   | 0.7970 |
| 0.1714        | 2.0   | 642  | 1.1443          | 0.7867   | 0.7795 |
| 0.1252        | 3.0   | 963  | 1.1800          | 0.8079   | 0.8089 |
| 0.1066        | 4.0   | 1284 | 1.3241          | 0.7973   | 0.7987 |
| 0.0817        | 5.0   | 1605 | 1.5002          | 0.7912   | 0.7937 |
| 0.0692        | 6.0   | 1926 | 1.4525          | 0.8033   | 0.8044 |
| 0.0529        | 7.0   | 2247 | 1.5662          | 0.7988   | 0.8000 |
| 0.0505        | 8.0   | 2568 | 1.6376          | 0.7958   | 0.7968 |
| 0.0341        | 9.0   | 2889 | 1.6486          | 0.7988   | 0.7989 |
| 0.0367        | 10.0  | 3210 | 1.6994          | 0.7852   | 0.7857 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3