metadata

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

wav2vec2-augmented-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: 0.4403
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