Instructions to use ittailup/distilgender-es-2M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ittailup/distilgender-es-2M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ittailup/distilgender-es-2M")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ittailup/distilgender-es-2M") model = AutoModelForSequenceClassification.from_pretrained("ittailup/distilgender-es-2M") - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- ittailup/issste
language:
- es
metrics:
- accuracy: 0.9951
widget:
- text: AGATA
- text: GABRIEL
Model Card
Overview
This model card provides details about a trained model, its training process, and evaluation metrics. This information ensures transparency and assists users in understanding the model's performance and behavior.
Training Details
- Training Epochs: The model was trained for 2 epochs.
- Training Steps: The model underwent 1856 training steps.
- Training Runtime: The model's training runtime was approximately 2680.184 seconds.
- Training Speed: The model trained at a rate of 0.692 steps per second and processed approximately 1417.813 samples per second.
- Learning Rate: The learning rate during training was approximately 0.0000095905.
- Training Loss: The average training loss recorded was approximately 0.0184, with a specific loss value of 0.023423514232553285.
Evaluation Details
- Evaluation Loss: The model achieved an evaluation loss of 0.017659155651926994.
- Evaluation Runtime: The evaluation process took approximately 23.8414 seconds.
- Evaluation Speed: The model was evaluated at a rate of 2.055 steps per second, processing approximately 4194.378 samples per second.
Performance Metrics
- Accuracy: The model achieved an accuracy of 0.9951 during evaluation.
- Precision: The precision of the model is approximately 0.9957234121187588.
- Recall: The model's recall is approximately 0.9956533216014078.
- F1-Score: The F1-Score for the model is approximately 0.995688365626595.