---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tluo_xml_roberta_base_amazon_review_sentiment_v4
  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. -->

# tluo_xml_roberta_base_amazon_review_sentiment_v4

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: 0.9589
- Accuracy: 0.6137

## 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: 1.5745609276104923e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 25
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1074        | 0.17  | 5000  | 1.0468          | 0.5493   |
| 1.0461        | 0.33  | 10000 | 1.0222          | 0.558    |
| 1.0245        | 0.5   | 15000 | 0.9776          | 0.5793   |
| 0.9876        | 0.67  | 20000 | 1.0327          | 0.571    |
| 1.0073        | 0.83  | 25000 | 0.9695          | 0.5807   |
| 0.9808        | 1.0   | 30000 | 1.0077          | 0.5857   |
| 0.9399        | 1.17  | 35000 | 1.0113          | 0.6043   |
| 0.8944        | 1.33  | 40000 | 0.9534          | 0.5947   |
| 0.908         | 1.5   | 45000 | 1.0155          | 0.5947   |
| 0.9238        | 1.67  | 50000 | 0.9813          | 0.597    |
| 0.8699        | 1.83  | 55000 | 0.9646          | 0.6027   |
| 0.8829        | 2.0   | 60000 | 0.9589          | 0.6137   |
| 0.8214        | 2.17  | 65000 | 1.0378          | 0.6017   |
| 0.8052        | 2.33  | 70000 | 1.0080          | 0.6003   |
| 0.7807        | 2.5   | 75000 | 1.0830          | 0.604    |
| 0.7927        | 2.67  | 80000 | 1.0225          | 0.6007   |
| 0.8358        | 2.83  | 85000 | 0.9989          | 0.5997   |
| 0.7899        | 3.0   | 90000 | 1.0108          | 0.6023   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2