metadata

language:
  - en
base_model: openai/wav2vec2
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: BANG WAV2VEC v1 (EN)
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Radio-Modified Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: en
          split: test
          args: 'config: en, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 99.57036953835787

BANG WAV2VEC v1 (EN)

This model is a fine-tuned version of openai/wav2vec2 on the Radio-Modified Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 261.3464
Wer: 99.5704

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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 6000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
206.0696	0.1667	1000	368.4753	98.1649
164.236	0.3333	2000	310.1212	98.1649
168.343	0.5	3000	299.5959	98.1649
165.9723	0.6667	4000	293.7289	98.1635
155.8457	0.8333	5000	265.2044	98.1635
155.6296	1.0	6000	261.3464	99.5704

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1