---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
datasets:
- indolem_sentiment
model-index:
- name: scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base
  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. -->

# scenario-normal-finetune-clf-data-indolem_sentiment-model-xlm-roberta-base

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the indolem_sentiment dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6171

## 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: 5e-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 | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.22  | 100  | 0.6046          |
| No log        | 0.44  | 200  | 0.6079          |
| No log        | 0.66  | 300  | 0.6091          |
| No log        | 0.88  | 400  | 0.6057          |
| 0.6278        | 1.1   | 500  | 0.6073          |
| 0.6278        | 1.32  | 600  | 0.6139          |
| 0.6278        | 1.54  | 700  | 0.6050          |
| 0.6278        | 1.76  | 800  | 0.6120          |
| 0.6278        | 1.98  | 900  | 0.6073          |
| 0.6138        | 2.2   | 1000 | 0.6066          |
| 0.6138        | 2.42  | 1100 | 0.6171          |


### Framework versions

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