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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: result1
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: 0.979381443298969
---
<!-- 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. -->
# result1
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: 1.1566
- Accuracy: 0.9794
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log | 0.9231 | 3 | 1.3671 | 0.9588 |
| No log | 1.8462 | 6 | 1.3125 | 0.9897 |
| No log | 2.7692 | 9 | 1.2705 | 0.9691 |
| 1.372 | 4.0 | 13 | 1.2335 | 0.9794 |
| 1.372 | 4.9231 | 16 | 1.2130 | 0.9897 |
| 1.372 | 5.8462 | 19 | 1.1962 | 0.9794 |
| 1.2696 | 6.7692 | 22 | 1.1803 | 0.9794 |
| 1.2696 | 8.0 | 26 | 1.1640 | 0.9794 |
| 1.2696 | 8.9231 | 29 | 1.1574 | 0.9794 |
| 1.208 | 9.2308 | 30 | 1.1566 | 0.9794 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.1.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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