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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-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: 0.83
---
<!-- 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-finetuned-gtzan
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7926
- Accuracy: 0.83
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0468 | 1.0 | 113 | 2.0109 | 0.41 |
| 1.6902 | 2.0 | 226 | 1.6493 | 0.5 |
| 1.0179 | 3.0 | 339 | 1.4098 | 0.59 |
| 1.1239 | 4.0 | 452 | 1.1319 | 0.67 |
| 0.7065 | 5.0 | 565 | 0.9650 | 0.73 |
| 0.546 | 6.0 | 678 | 0.9210 | 0.75 |
| 0.535 | 7.0 | 791 | 0.7329 | 0.81 |
| 0.3793 | 8.0 | 904 | 0.5348 | 0.86 |
| 0.6647 | 9.0 | 1017 | 0.6605 | 0.84 |
| 0.3996 | 10.0 | 1130 | 0.7797 | 0.83 |
| 0.432 | 11.0 | 1243 | 0.7763 | 0.83 |
| 0.0538 | 12.0 | 1356 | 0.7716 | 0.84 |
| 0.0858 | 13.0 | 1469 | 0.7953 | 0.82 |
| 0.3906 | 14.0 | 1582 | 0.7821 | 0.84 |
| 0.2496 | 15.0 | 1695 | 0.9718 | 0.83 |
| 0.13 | 16.0 | 1808 | 0.7773 | 0.85 |
| 0.1103 | 17.0 | 1921 | 0.6670 | 0.88 |
| 0.1443 | 18.0 | 2034 | 0.8843 | 0.84 |
| 0.0083 | 19.0 | 2147 | 0.7977 | 0.84 |
| 0.0086 | 20.0 | 2260 | 0.7926 | 0.83 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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