metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- vivos
metrics:
- wer
model-index:
- name: working
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: 0.19310434387377443
working
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: 0.2735
- Wer: 0.1931
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.8333 | 1.0274 | 300 | 3.7834 | 1.0 |
| 2.3412 | 2.0548 | 600 | 0.8215 | 0.5481 |
| 0.6754 | 3.0822 | 900 | 0.4963 | 0.3560 |
| 0.4809 | 4.1096 | 1200 | 0.3978 | 0.2980 |
| 0.395 | 5.1370 | 1500 | 0.3535 | 0.2613 |
| 0.3453 | 6.1644 | 1800 | 0.3192 | 0.2318 |
| 0.3024 | 7.1918 | 2100 | 0.2948 | 0.2166 |
| 0.2683 | 8.2192 | 2400 | 0.2844 | 0.2043 |
| 0.2468 | 9.2466 | 2700 | 0.2785 | 0.1947 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1