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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: vivos
type: vivos
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.014473684210526316
---
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# wav2vec2-base-finetuned-ks
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the vivos dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0319
- Accuracy: 0.0145
## 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: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log | 0.9990 | 364 | 4.0319 | 0.0145 |
| 3.1633 | 1.9979 | 728 | 4.7572 | 0.0013 |
| 0.9306 | 2.9969 | 1092 | 5.4901 | 0.0 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.19.1
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