README.md

metadata

license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
  - generated_from_trainer
datasets:
  - voxpopuli
metrics:
  - wer
model-index:
  - name: wav2vec2-efeat-300m-norwegian-colab
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: voxpopuli
          type: voxpopuli
          config: fi
          split: test
          args: fi
        metrics:
          - name: Wer
            type: wer
            value: 0.5082158970645575

wav2vec2-efeat-300m-norwegian-colab

This model is a fine-tuned version of facebook/wav2vec2-lv-60-espeak-cv-ft on the voxpopuli dataset. It achieves the following results on the evaluation set:

• Loss: 2050.9434
• Wer: 0.5082

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: 1000
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1368.1253	2.57	400	2050.9434	0.5082

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0