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---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-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: 0.87
---
<!-- 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. -->
# wav2vec2-base-960h-finetuned-gtzan
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5055
- Accuracy: 0.87
## 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: 16
- eval_batch_size: 16
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2648 | 1.0 | 57 | 2.2400 | 0.15 |
| 2.167 | 2.0 | 114 | 2.1032 | 0.17 |
| 1.8573 | 3.0 | 171 | 1.7658 | 0.32 |
| 1.5347 | 4.0 | 228 | 1.6620 | 0.45 |
| 1.6134 | 5.0 | 285 | 1.5017 | 0.49 |
| 1.2903 | 6.0 | 342 | 1.4639 | 0.49 |
| 1.29 | 7.0 | 399 | 1.1893 | 0.66 |
| 1.1094 | 8.0 | 456 | 1.1425 | 0.67 |
| 1.1023 | 9.0 | 513 | 1.0173 | 0.72 |
| 0.9244 | 10.0 | 570 | 0.9069 | 0.79 |
| 0.7764 | 11.0 | 627 | 0.9314 | 0.74 |
| 0.6899 | 12.0 | 684 | 0.7919 | 0.78 |
| 0.6033 | 13.0 | 741 | 0.7145 | 0.8 |
| 0.4834 | 14.0 | 798 | 0.8896 | 0.76 |
| 0.4409 | 15.0 | 855 | 0.7083 | 0.82 |
| 0.3653 | 16.0 | 912 | 0.5633 | 0.83 |
| 0.3986 | 17.0 | 969 | 0.5475 | 0.89 |
| 0.2725 | 18.0 | 1026 | 0.5044 | 0.87 |
| 0.3569 | 19.0 | 1083 | 0.5044 | 0.85 |
| 0.2089 | 20.0 | 1140 | 0.5055 | 0.87 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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