README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: URDU-ASR
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: ur
          split: test
          args: ur
        metrics:
          - name: Wer
            type: wer
            value: 0.49680838717165077

URDU-ASR

This model was trained from scratch on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.6632
• Wer: 0.4968
• Cer: 0.2099

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.85,0.9) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.9625	1.0	341	0.7371	0.5348	0.2190
0.2156	2.0	683	0.7057	0.5103	0.2169
0.2451	3.0	1024	0.6654	0.5161	0.2214
0.199	4.0	1366	0.6707	0.5089	0.2153
0.1657	4.99	1705	0.6632	0.4968	0.2099

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1