File size: 2,603 Bytes
a615163 |
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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan-bs-16
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.88
---
<!-- 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-bs-16
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: 0.5497
- Accuracy: 0.88
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0557 | 1.0 | 57 | 1.9783 | 0.34 |
| 1.6173 | 2.0 | 114 | 1.6407 | 0.55 |
| 1.3884 | 3.0 | 171 | 1.2228 | 0.65 |
| 1.1082 | 4.0 | 228 | 1.0989 | 0.7 |
| 0.9112 | 5.0 | 285 | 0.8724 | 0.8 |
| 0.7985 | 6.0 | 342 | 0.8715 | 0.76 |
| 0.5456 | 7.0 | 399 | 0.6832 | 0.82 |
| 0.4842 | 8.0 | 456 | 0.6566 | 0.85 |
| 0.3419 | 9.0 | 513 | 0.6485 | 0.84 |
| 0.5821 | 10.0 | 570 | 0.5636 | 0.85 |
| 0.2112 | 11.0 | 627 | 0.4572 | 0.89 |
| 0.2005 | 12.0 | 684 | 0.5405 | 0.87 |
| 0.1314 | 13.0 | 741 | 0.4695 | 0.9 |
| 0.0866 | 14.0 | 798 | 0.5545 | 0.88 |
| 0.0594 | 15.0 | 855 | 0.5497 | 0.88 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
|