metadata
tags:
- generated_from_trainer
datasets:
- amazon_reviews_multi
metrics:
- accuracy
model_index:
- name: >-
roberta-base-bne-finetuned-amazon_reviews_multi-finetuned-amazon_reviews_multi
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: amazon_reviews_multi
type: amazon_reviews_multi
args: es
metric:
name: Accuracy
type: accuracy
value: 0.9285
roberta-base-bne-finetuned-amazon_reviews_multi-finetuned-amazon_reviews_multi
This model was trained from scratch on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:
- Loss: 0.3595
- Accuracy: 0.9285
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 |
---|---|---|---|---|
0.103 | 1.0 | 1250 | 0.2864 | 0.928 |
0.0407 | 2.0 | 2500 | 0.3595 | 0.9285 |
Framework versions
- Transformers 4.9.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3