README.md

metadata

license: apache-2.0
base_model: facebook/wav2vec2-lv-60-espeak-cv-ft
tags:
  - generated_from_trainer
datasets:
  - nb_samtale
metrics:
  - wer
model-index:
  - name: cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: nb_samtale
          type: nb_samtale
          config: annotations
          split: test
          args: annotations
        metrics:
          - name: Wer
            type: wer
            value: 0.7063259628056816

cs2no-wav2vec2-large-xls-r-300m-cs-colab-phoneme

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

• Loss: 4.9174
• Wer: 0.7063

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: 1e-05
• 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: 50
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.82	16.67	100	5.2819	0.7336
2.8834	33.33	200	4.9424	0.7091
2.5387	50.0	300	4.9174	0.7063

Framework versions

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