Instructions to use Lucyan85/beto-sarcasmo-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lucyan85/beto-sarcasmo-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Lucyan85/beto-sarcasmo-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Lucyan85/beto-sarcasmo-sentiment") model = AutoModelForSequenceClassification.from_pretrained("Lucyan85/beto-sarcasmo-sentiment") - Notebooks
- Google Colab
- Kaggle
beto-sarcasmo-sentiment
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0201
- Accuracy: 0.9965
- F1: 0.9956
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.0055 | 1.0 | 72 | 0.7659 | 0.8376 | 0.7929 |
| 0.6397 | 2.0 | 144 | 0.7527 | 0.8625 | 0.8150 |
| 0.2516 | 3.0 | 216 | 0.8466 | 0.8704 | 0.8276 |
| 0.1570 | 4.0 | 288 | 1.0872 | 0.8708 | 0.8324 |
| 0.0476 | 5.0 | 360 | 1.1780 | 0.8739 | 0.8368 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2
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Model tree for Lucyan85/beto-sarcasmo-sentiment
Base model
dccuchile/bert-base-spanish-wwm-cased