File size: 3,070 Bytes
611b2ce |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 |
---
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
|