---
base_model: citizenlab/twitter-xlm-roberta-base-sentiment-finetunned
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hihu3
  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. -->

# hihu3

This model is a fine-tuned version of [citizenlab/twitter-xlm-roberta-base-sentiment-finetunned](https://huggingface.co/citizenlab/twitter-xlm-roberta-base-sentiment-finetunned) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7639
- Accuracy: 0.7314

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7062        | 1.0   | 1648 | 0.6899          | 0.7165   |
| 0.6047        | 2.0   | 3296 | 0.6696          | 0.7271   |
| 0.5057        | 3.0   | 4944 | 0.6754          | 0.7341   |
| 0.4325        | 4.0   | 6592 | 0.7141          | 0.7305   |
| 0.4025        | 5.0   | 8240 | 0.7639          | 0.7314   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cpu
- Datasets 2.14.4
- Tokenizers 0.13.0