---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: V2_20230929-4-xlm-roberta-base-new
  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. -->

# V2_20230929-4-xlm-roberta-base-new

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:
- Accuracy: 0.4980
- Loss: 2.6341

## 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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.4422        | 1.38  | 200  | 0.2888   | 4.2369          |
| 3.9018        | 2.76  | 400  | 0.3333   | 3.9767          |
| 3.5709        | 4.14  | 600  | 0.3669   | 3.5533          |
| 3.3829        | 5.52  | 800  | 0.3891   | 3.3396          |
| 3.2242        | 6.9   | 1000 | 0.4244   | 3.0648          |
| 3.0837        | 8.28  | 1200 | 0.4515   | 3.2200          |
| 2.9448        | 9.66  | 1400 | 0.4637   | 2.8563          |
| 2.8529        | 11.03 | 1600 | 0.4664   | 2.9343          |
| 2.8343        | 12.41 | 1800 | 0.4498   | 3.1041          |
| 2.813         | 13.79 | 2000 | 0.4980   | 2.6341          |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3