Distilhubert Finetuned Babycry V7

🚀 distilhubert-finetuned-babycry-v7

This model, distilhubert-finetuned-babycry-v7, is a fine - tuned version of [ntu - spml/distilhubert](https://huggingface.co/ntu - spml/distilhubert) on an unknown dataset. It offers high - performance results in relevant evaluations, which can be useful for tasks such as baby cry classification.

🚀 Quick Start

This section provides a high - level overview of the model. For more detailed usage, please refer to the official documentation of the transformers library.

✨ Features

• Fine - tuned Model: Based on [ntu - spml/distilhubert](https://huggingface.co/ntu - spml/distilhubert), it has been fine - tuned to better adapt to specific tasks.
• Multiple Evaluation Metrics: Achieves good results in multiple evaluation metrics, including accuracy, F1, precision, and recall.

📚 Documentation

Model Performance

This model achieves the following results on the evaluation set:

• Loss: 0.5864
• Accuracy: {'accuracy': 0.8695652173913043}
• F1: 0.8089
• Precision: 0.7561
• Recall: 0.8696

Training Procedure

Training Hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.03
• num_epochs: 8

Training Results

Framework Versions

• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Tokenizers 0.19.1

📄 License

This project is licensed under the Apache - 2.0 license.