|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- vivos |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-vivos-asr |
|
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: 0.20053544110147883 |
|
--- |
|
|
|
<!-- 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-vivos-asr |
|
|
|
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: 0.3151 |
|
- Wer: 0.2005 |
|
|
|
## 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: 0.0001 |
|
- 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: linear |
|
- lr_scheduler_warmup_steps: 300 |
|
- num_epochs: 20 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 7.4472 | 2.0 | 146 | 4.1025 | 1.0 | |
|
| 3.4729 | 4.0 | 292 | 3.6046 | 1.0 | |
|
| 2.8216 | 6.0 | 438 | 1.4275 | 0.8461 | |
|
| 0.8343 | 8.0 | 584 | 0.5637 | 0.3727 | |
|
| 0.4258 | 10.0 | 730 | 0.4272 | 0.2877 | |
|
| 0.3012 | 12.0 | 876 | 0.3548 | 0.2370 | |
|
| 0.2445 | 14.0 | 1022 | 0.3371 | 0.2230 | |
|
| 0.2328 | 16.0 | 1168 | 0.3269 | 0.2119 | |
|
| 0.1831 | 18.0 | 1314 | 0.3204 | 0.2058 | |
|
| 0.1664 | 20.0 | 1460 | 0.3151 | 0.2005 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
