|
--- |
|
license: apache-2.0 |
|
base_model: openai/whisper-large-v3 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: whisper-large-v3-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: 0.94 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# whisper-large-v3-finetuned-gtzan |
|
|
|
This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2657 |
|
- Accuracy: 0.94 |
|
|
|
## 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: 4e-05 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 16 |
|
- total_eval_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.1646 | 0.5 | 28 | 1.8012 | 0.55 | |
|
| 1.0152 | 1.0 | 56 | 0.8618 | 0.79 | |
|
| 1.1129 | 1.49 | 84 | 0.7426 | 0.8 | |
|
| 0.8163 | 1.99 | 112 | 0.8078 | 0.75 | |
|
| 0.4374 | 2.49 | 140 | 0.6259 | 0.81 | |
|
| 0.4607 | 2.99 | 168 | 0.5424 | 0.83 | |
|
| 0.4225 | 3.48 | 196 | 0.3723 | 0.89 | |
|
| 0.1769 | 3.98 | 224 | 0.3517 | 0.9 | |
|
| 0.0927 | 4.48 | 252 | 0.3385 | 0.89 | |
|
| 0.0159 | 4.98 | 280 | 0.3985 | 0.88 | |
|
| 0.0119 | 5.48 | 308 | 0.4626 | 0.9 | |
|
| 0.029 | 5.97 | 336 | 0.4292 | 0.91 | |
|
| 0.0064 | 6.47 | 364 | 0.2710 | 0.93 | |
|
| 0.0057 | 6.97 | 392 | 0.2665 | 0.93 | |
|
| 0.0048 | 7.47 | 420 | 0.2784 | 0.93 | |
|
| 0.0049 | 7.96 | 448 | 0.2550 | 0.94 | |
|
| 0.0049 | 8.46 | 476 | 0.3011 | 0.94 | |
|
| 0.0044 | 8.96 | 504 | 0.2759 | 0.94 | |
|
| 0.0045 | 9.46 | 532 | 0.2661 | 0.94 | |
|
| 0.0048 | 9.96 | 560 | 0.2657 | 0.94 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.2.0+cu121 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.1 |
|
|
