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---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: facebook_wav2vec2-large_October_03_2023_05h34PM
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9743347801471975
---
<!-- 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. -->
# facebook_wav2vec2-large_October_03_2023_05h34PM
This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1318
- Accuracy: 0.9743
## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4214 | 1.0 | 121 | 0.3650 | 0.7932 |
| 0.1959 | 2.0 | 242 | 0.2588 | 0.8960 |
| 0.1365 | 3.0 | 363 | 0.0732 | 0.9713 |
| 0.1003 | 4.0 | 484 | 0.0849 | 0.9719 |
| 0.0806 | 5.0 | 605 | 0.2170 | 0.9381 |
| 0.0588 | 6.0 | 726 | 0.0738 | 0.9760 |
| 0.0472 | 7.0 | 847 | 0.2083 | 0.9409 |
| 0.0505 | 8.0 | 968 | 0.1020 | 0.9760 |
| 0.0427 | 9.0 | 1089 | 0.0626 | 0.9809 |
| 0.0285 | 10.0 | 1210 | 0.1062 | 0.9732 |
| 0.0286 | 11.0 | 1331 | 0.1068 | 0.9738 |
| 0.0231 | 12.0 | 1452 | 0.1137 | 0.9755 |
| 0.0232 | 13.0 | 1573 | 0.0783 | 0.9815 |
| 0.0158 | 14.0 | 1694 | 0.1138 | 0.9755 |
| 0.0164 | 15.0 | 1815 | 0.1318 | 0.9743 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.2.0.dev20230927+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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