metadata
base_model: facebook/wav2vec2-base
datasets:
- vivos
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-vivos
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: vivos
type: vivos
config: default
split: None
args: default
metrics:
- type: wer
value: 0.2342930262316059
name: Wer
wav2vec2-vivos
This model is a fine-tuned version of facebook/wav2vec2-base on the vivos dataset. It achieves the following results on the evaluation set:
- Loss: 0.4598
- Wer: 0.2343
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: linear
- lr_scheduler_warmup_ratio: 0.25
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.8271 | 2.0 | 146 | 3.8747 | 1.0 |
| 3.4616 | 4.0 | 292 | 3.5849 | 1.0 |
| 3.35 | 6.0 | 438 | 2.6294 | 0.9997 |
| 1.1993 | 8.0 | 584 | 0.6472 | 0.4255 |
| 0.4734 | 10.0 | 730 | 0.5342 | 0.3258 |
| 0.3156 | 12.0 | 876 | 0.4651 | 0.2758 |
| 0.2392 | 14.0 | 1022 | 0.4690 | 0.2573 |
| 0.2183 | 16.0 | 1168 | 0.4601 | 0.2434 |
| 0.164 | 18.0 | 1314 | 0.4619 | 0.2379 |
| 0.1452 | 20.0 | 1460 | 0.4598 | 0.2343 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1