metadata
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: []
distilhubert-finetuned-cry-detector
This model is a fine-tuned version of ntu-spml/distilhubert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0338
- Accuracy: 0.9912
- Precision: 0.9912
- Recall: 0.9912
- F1: 0.9912
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 | 0.1197 | 0.9538 | 0.9535 | 0.9538 | 0.9536 |
| No log | 1.9912 | 170 | 0.0601 | 0.9832 | 0.9831 | 0.9832 | 0.9831 |
| No log | 2.9985 | 256 | 0.0506 | 0.9868 | 0.9868 | 0.9868 | 0.9868 |
| No log | 3.9941 | 341 | 0.0461 | 0.9861 | 0.9864 | 0.9861 | 0.9862 |
| No log | 4.9898 | 426 | 0.0439 | 0.9890 | 0.9891 | 0.9890 | 0.9890 |
| 0.0779 | 5.9971 | 512 | 0.0396 | 0.9905 | 0.9905 | 0.9905 | 0.9905 |
| 0.0779 | 6.9927 | 597 | 0.0350 | 0.9919 | 0.9919 | 0.9919 | 0.9919 |
| 0.0779 | 8.0 | 683 | 0.0335 | 0.9912 | 0.9912 | 0.9912 | 0.9912 |
| 0.0779 | 8.9956 | 768 | 0.0337 | 0.9912 | 0.9912 | 0.9912 | 0.9912 |
| 0.0779 | 9.9561 | 850 | 0.0338 | 0.9912 | 0.9912 | 0.9912 | 0.9912 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1