metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: faiq-wav2vec2-large-xlsr-indo-demo-rtx4090-batch32
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: id
          split: test
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 0.4295751710018147

faiq-wav2vec2-large-xlsr-indo-demo-rtx4090-batch32

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.3705
Wer: 0.4296

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: 0.0003
train_batch_size: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.559	5.84	400	2.8099	1.0
0.9265	11.68	800	0.3847	0.5260
0.2592	17.52	1200	0.3658	0.4685
0.176	23.36	1600	0.3862	0.4422
0.1451	29.2	2000	0.3705	0.4296

Framework versions

Transformers 4.28.0
Pytorch 2.0.1
Datasets 2.6.1
Tokenizers 0.13.3