---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-results-concat
  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. -->

# test-results-concat

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: 0.9408
- Accuracy: 0.6012

## 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: 8
- eval_batch_size: 8
- seed: 123
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0408        | 0.33  | 5000  | 0.9773          | 0.5697   |
| 0.9442        | 0.67  | 10000 | 0.9701          | 0.5853   |
| 0.9579        | 1.0   | 15000 | 0.9502          | 0.5895   |
| 0.8867        | 1.33  | 20000 | 0.9467          | 0.5897   |
| 0.8819        | 1.67  | 25000 | 0.9371          | 0.5893   |
| 0.8748        | 2.0   | 30000 | 0.9408          | 0.6012   |
| 0.7759        | 2.33  | 35000 | 0.9734          | 0.5968   |
| 0.7599        | 2.67  | 40000 | 0.9722          | 0.5948   |
| 0.7626        | 3.0   | 45000 | 0.9654          | 0.5975   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1