metadata
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
datasets:
- muchocine
metrics:
- accuracy
model-index:
- name: bert-base-uncased-es-sentiment-analysis
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: muchocine
type: muchocine
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.792258064516129
bert-base-uncased-es-sentiment-analysis
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on the muchocine dataset. It achieves the following results on the evaluation set:
- Loss: 0.9713
- Accuracy: 0.7923
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.541 | 1.0 | 49 | 0.4618 | 0.7781 |
| 0.3157 | 2.0 | 98 | 0.4989 | 0.7742 |
| 0.1294 | 3.0 | 147 | 0.6931 | 0.8 |
| 0.0541 | 4.0 | 196 | 0.8284 | 0.7935 |
| 0.0254 | 5.0 | 245 | 0.9713 | 0.7923 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1