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---
license: apache-2.0
base_model: bookbot/distil-wav2vec2-adult-child-cls-37m
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distil-wav2vec2-adult-child-cls-37m-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.83
---
<!-- 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. -->
# distil-wav2vec2-adult-child-cls-37m-finetuned-gtzan
This model is a fine-tuned version of [bookbot/distil-wav2vec2-adult-child-cls-37m](https://huggingface.co/bookbot/distil-wav2vec2-adult-child-cls-37m) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7224
- Accuracy: 0.83
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8362 | 1.0 | 112 | 1.6074 | 0.51 |
| 1.1668 | 1.99 | 224 | 1.1540 | 0.65 |
| 1.0829 | 3.0 | 337 | 0.8698 | 0.7 |
| 0.9575 | 4.0 | 449 | 0.7932 | 0.71 |
| 0.6609 | 4.99 | 561 | 0.6541 | 0.81 |
| 0.3644 | 6.0 | 674 | 0.6870 | 0.79 |
| 0.6608 | 6.99 | 786 | 0.6536 | 0.81 |
| 0.2477 | 8.0 | 899 | 0.7209 | 0.82 |
| 0.376 | 9.0 | 1011 | 0.5980 | 0.86 |
| 0.1268 | 9.97 | 1120 | 0.7224 | 0.83 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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