---
library_name: transformers
license: mit
base_model: vinai/phobert-base
tags:
- generated_from_trainer
model-index:
- name: clapAI/roberta-base-multilingual-sentiment
  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. -->

# clapAI/roberta-base-multilingual-sentiment

This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7236
- Micro F1: 31.1953
- Micro Precision: 31.1953
- Micro Recall: 31.1953
- Macro F1: 6.7937
- Macro Precision: 4.4565
- Macro Recall: 14.2857

## 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: 512
- eval_batch_size: 512
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 1024
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Micro F1 | Micro Precision | Micro Recall | Macro F1 | Macro Precision | Macro Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|
| 1.9456        | 1.0    | 6    | 1.9434          | 18.2216  | 18.2216         | 18.2216      | 9.4327   | 17.2520         | 13.4610      |
| 1.7519        | 2.0    | 12   | 1.9434          | 18.2216  | 18.2216         | 18.2216      | 9.4327   | 17.2520         | 13.4610      |
| 1.7517        | 3.0    | 18   | 1.9434          | 18.2216  | 18.2216         | 18.2216      | 9.4327   | 17.2520         | 13.4610      |
| 1.7491        | 4.0    | 24   | 1.7236          | 31.1953  | 31.1953         | 31.1953      | 6.7937   | 4.4565          | 14.2857      |
| 1.6352        | 4.1818 | 25   | 1.7158          | 31.1953  | 31.1953         | 31.1953      | 6.7937   | 4.4565          | 14.2857      |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.4.0+cu121
- Datasets 2.15.0
- Tokenizers 0.21.1