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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- wer
model-index:
- name: wav2vec2-augmented-vivos
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: vivos
type: vivos
config: default
split: None
args: default
metrics:
- name: Wer
type: wer
value: 0.2447200155008719
---
<!-- 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-augmented-vivos
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: 0.4403
- Wer: 0.2447
## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 8
- 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: cosine
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.6691 | 2.0 | 146 | 4.0324 | 1.0 |
| 3.4795 | 4.0 | 292 | 3.6294 | 1.0 |
| 3.4178 | 6.0 | 438 | 3.4910 | 1.0 |
| 1.8415 | 8.0 | 584 | 0.7926 | 0.5287 |
| 0.5336 | 10.0 | 730 | 0.5809 | 0.3677 |
| 0.3349 | 12.0 | 876 | 0.4679 | 0.2853 |
| 0.2424 | 14.0 | 1022 | 0.4440 | 0.2680 |
| 0.2193 | 16.0 | 1168 | 0.4420 | 0.2536 |
| 0.1627 | 18.0 | 1314 | 0.4373 | 0.2455 |
| 0.1532 | 20.0 | 1460 | 0.4403 | 0.2447 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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