---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 20230928-10-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. -->

# 20230928-10-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: 0.4847
- Loss: nan

## 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: 10

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 4.5116        | 0.46  | 200  | 0.2970   | nan             |
| 3.9887        | 0.91  | 400  | 0.3086   | 4.0522          |
| 3.9101        | 1.37  | 600  | 0.3138   | nan             |
| 3.7634        | 1.82  | 800  | 0.3184   | 3.7682          |
| 3.4413        | 2.28  | 1000 | 0.3977   | 2.9317          |
| 3.4478        | 2.73  | 1200 | 0.4102   | nan             |
| 3.4179        | 3.19  | 1400 | 0.3790   | 3.2163          |
| 3.2165        | 3.64  | 1600 | 0.4435   | 2.7062          |
| 3.1388        | 4.1   | 1800 | 0.4540   | 2.8629          |
| 3.0987        | 4.56  | 2000 | 0.4509   | nan             |
| 3.0614        | 5.01  | 2200 | 0.4894   | nan             |
| 3.1399        | 5.47  | 2400 | 0.5337   | nan             |
| 3.0387        | 5.92  | 2600 | 0.4667   | 3.0331          |
| 2.9728        | 6.38  | 2800 | 0.4571   | nan             |
| 2.9138        | 6.83  | 3000 | 0.4306   | 2.8179          |
| 2.9157        | 7.29  | 3200 | 0.4520   | nan             |
| 2.8103        | 7.74  | 3400 | 0.5      | nan             |
| 2.7693        | 8.2   | 3600 | 0.4841   | 2.9349          |
| 2.8204        | 8.66  | 3800 | 0.4727   | 2.7438          |
| 2.7711        | 9.11  | 4000 | 0.5123   | 2.6654          |
| 2.7196        | 9.57  | 4200 | 0.4847   | nan             |


### Framework versions

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