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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_custom2_model
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9166666666666666
---
<!-- 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. -->
# my_custom2_model
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4030
- Accuracy: 0.9167
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1798 | 1.0 | 6 | 0.4439 | 0.75 |
| 0.2051 | 2.0 | 12 | 0.5505 | 0.5833 |
| 0.1612 | 3.0 | 18 | 0.1884 | 0.9167 |
| 0.2032 | 4.0 | 24 | 0.2759 | 0.9167 |
| 0.1803 | 5.0 | 30 | 0.5196 | 0.8333 |
| 0.0478 | 6.0 | 36 | 0.3214 | 0.9167 |
| 0.1159 | 7.0 | 42 | 0.3311 | 0.9167 |
| 0.031 | 8.0 | 48 | 0.6261 | 0.8333 |
| 0.0263 | 9.0 | 54 | 0.3536 | 0.9167 |
| 0.2505 | 10.0 | 60 | 0.3637 | 0.9167 |
| 0.018 | 11.0 | 66 | 0.3721 | 0.9167 |
| 0.0167 | 12.0 | 72 | 0.6487 | 0.8333 |
| 0.0154 | 13.0 | 78 | 0.7422 | 0.8333 |
| 0.0144 | 14.0 | 84 | 0.7221 | 0.8333 |
| 0.0129 | 15.0 | 90 | 0.5876 | 0.8333 |
| 0.0123 | 16.0 | 96 | 0.4041 | 0.9167 |
| 0.0118 | 17.0 | 102 | 0.4000 | 0.9167 |
| 0.0115 | 18.0 | 108 | 0.4015 | 0.9167 |
| 0.0112 | 19.0 | 114 | 0.4025 | 0.9167 |
| 0.011 | 20.0 | 120 | 0.4030 | 0.9167 |
### Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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