metadata
license: apache-2.0
base_model: vpingale07/distilhubert-v2-v4
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: vpingale07/distilhubert-v2-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: 0.78
vpingale07/distilhubert-v2-finetuned-gtzan
This model is a fine-tuned version of vpingale07/distilhubert-v2-v4 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 1.5112
- Accuracy: 0.78
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.0737 | 1.0 | 113 | 1.7242 | 0.8 |
0.2159 | 2.0 | 226 | 1.3651 | 0.84 |
0.0001 | 3.0 | 339 | 1.4341 | 0.77 |
0.0001 | 4.0 | 452 | 1.5112 | 0.78 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2