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---
license: apache-2.0
base_model: BSC-TeMU/roberta-base-bne
tags:
- generated_from_trainer
datasets:
- multilingual-sentiments
metrics:
- accuracy
model-index:
- name: roberta-base-bne-finetuned-amazon_reviews_multi
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: multilingual-sentiments
type: multilingual-sentiments
config: spanish
split: validation
args: spanish
metrics:
- name: Accuracy
type: accuracy
value: 0.6882716049382716
---
<!-- 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. -->
# roberta-base-bne-finetuned-amazon_reviews_multi
This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co./BSC-TeMU/roberta-base-bne) on the multilingual-sentiments dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6935
- Accuracy: 0.6883
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.786 | 1.0 | 115 | 0.6998 | 0.6914 |
| 0.474 | 2.0 | 230 | 0.6935 | 0.6883 |
### Framework versions
- Transformers 4.35.0
- Pytorch 1.13.1+cu117
- Datasets 2.14.6
- Tokenizers 0.14.1
|