README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: wav2vec2-xlsr-cv-11-layer
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: nan-tw
          split: test
          args: nan-tw
        metrics:
          - type: wer
            value: 1.0165016501650166
            name: Wer

wav2vec2-xlsr-cv-11-layer

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: 5.4908
• Wer: 1.0165

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: 0.003
• 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: 40
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
19.3425	8.0808	400	5.2991	1.0
4.0894	16.1616	800	5.5709	1.0
3.8676	24.2424	1200	5.5382	1.0055
3.7673	32.3232	1600	5.4908	1.0165

Framework versions

• Transformers 4.41.2
• Pytorch 2.1.2
• Datasets 2.19.2
• Tokenizers 0.19.1