|
--- |
|
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-multi-sentiment |
|
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: 0.7222222222222222 |
|
--- |
|
|
|
<!-- 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-multi-sentiment |
|
|
|
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: 0.7635 |
|
- Accuracy: 0.7222 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.6192 | 1.0 | 115 | 0.6712 | 0.7099 | |
|
| 0.217 | 2.0 | 230 | 0.7635 | 0.7222 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 1.13.1+cu117 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
