README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice
metrics:
  - wer
model-index:
  - name: hello_world
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice
          type: common_voice
          config: mn
          split: test
          args: mn
        metrics:
          - name: Wer
            type: wer
            value: 0.4679207811551829

hello_world

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

• Loss: 0.8235
• Wer: 0.4679

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: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• 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
2.1725	6.78	400	0.8343	0.5449
0.1406	13.56	800	0.8587	0.5158
0.1013	20.34	1200	0.8260	0.4990
0.0701	27.12	1600	0.8235	0.4679

Framework versions

• Transformers 4.30.1
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3