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update model card README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xlsr-53-AsanteTwi-05
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: tw
          split: test
          args: tw
        metrics:
          - name: Wer
            type: wer
            value: 0.75

wav2vec2-large-xlsr-53-AsanteTwi-05

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7657
  • Wer: 0.75

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: 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: 200
  • num_epochs: 150

Training results

Training Loss Epoch Step Validation Loss Wer
2.2241 16.67 100 2.1317 1.0
1.5168 33.33 200 1.1019 0.8125
0.7964 50.0 300 0.7658 0.75
0.4985 66.67 400 0.6807 0.625
0.3885 83.33 500 0.7197 0.5625
0.3269 100.0 600 0.7616 0.5625
0.2625 116.67 700 0.7000 0.6875
0.2595 133.33 800 0.7425 0.6875
0.2388 150.0 900 0.7657 0.75

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3