---
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilhubert-finetuned-cry-detector
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilhubert-finetuned-cry-detector

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0404
- Accuracy: 0.9905
- Precision: 0.9906
- Recall: 0.9905
- F1: 0.9905

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 123
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.001
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.9956 | 85   | 0.1607          | 0.9429   | 0.9455    | 0.9429 | 0.9435 |
| No log        | 1.9912 | 170  | 0.1011          | 0.9670   | 0.9669    | 0.9670 | 0.9669 |
| No log        | 2.9985 | 256  | 0.0582          | 0.9853   | 0.9857    | 0.9853 | 0.9854 |
| No log        | 3.9941 | 341  | 0.0424          | 0.9883   | 0.9884    | 0.9883 | 0.9883 |
| No log        | 4.9898 | 426  | 0.0489          | 0.9868   | 0.9870    | 0.9868 | 0.9869 |
| 0.0815        | 5.9971 | 512  | 0.0408          | 0.9883   | 0.9883    | 0.9883 | 0.9883 |
| 0.0815        | 6.9927 | 597  | 0.0395          | 0.9890   | 0.9891    | 0.9890 | 0.9890 |
| 0.0815        | 8.0    | 683  | 0.0400          | 0.9905   | 0.9906    | 0.9905 | 0.9905 |
| 0.0815        | 8.9956 | 768  | 0.0406          | 0.9905   | 0.9906    | 0.9905 | 0.9905 |
| 0.0815        | 9.9561 | 850  | 0.0404          | 0.9905   | 0.9906    | 0.9905 | 0.9905 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1