metadata
license: apache-2.0
base_model: yuval6967/wav2vec2-base-finetuned-gtzan
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan-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
wav2vec2-base-finetuned-gtzan-finetuned-gtzan
This model is a fine-tuned version of yuval6967/wav2vec2-base-finetuned-gtzan on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 1.3065
- 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6708 | 0.9956 | 112 | 1.2056 | 0.75 |
0.6752 | 2.0 | 225 | 1.1245 | 0.78 |
0.1894 | 2.9956 | 337 | 1.0640 | 0.81 |
0.2192 | 4.0 | 450 | 1.3034 | 0.76 |
0.2675 | 4.9956 | 562 | 1.0633 | 0.81 |
0.1237 | 6.0 | 675 | 1.3065 | 0.78 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1