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---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-donateacry
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8820224719101124
---
<!-- 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-donateacry
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4880
- Accuracy: 0.8820
## 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: 0.001
- 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: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 0.9888 | 11 | 0.9569 | 0.7135 |
| No log | 1.9775 | 22 | 0.8898 | 0.6798 |
| No log | 2.9663 | 33 | 0.7790 | 0.7528 |
| No log | 3.9551 | 44 | 0.7517 | 0.8258 |
| No log | 4.9438 | 55 | 0.6255 | 0.8539 |
| No log | 5.9326 | 66 | 0.6212 | 0.8258 |
| No log | 6.9213 | 77 | 0.5533 | 0.8596 |
| No log | 8.0 | 89 | 0.6533 | 0.8427 |
| No log | 8.9888 | 100 | 0.5997 | 0.8539 |
| No log | 9.9775 | 111 | 0.5749 | 0.8764 |
| No log | 10.9663 | 122 | 0.4880 | 0.8820 |
| No log | 11.8652 | 132 | 0.4965 | 0.8820 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
|