README.md

metadata

license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
datasets:
  - common_voice_16_1
metrics:
  - wer
model-index:
  - name: wav2vec2-large-mms-1b-yoruba-test
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_16_1
          type: common_voice_16_1
          config: yo
          split: test
          args: yo
        metrics:
          - name: Wer
            type: wer
            value: 0.6802364381733245

wav2vec2-large-mms-1b-yoruba-test

This model is a fine-tuned version of facebook/mms-1b-all on the common_voice_16_1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.6682
• Wer: 0.6802

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: 0.001
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.8923	0.77	100	0.7710	0.7413
0.7507	1.54	200	0.7249	0.7585
0.7033	2.31	300	0.7105	0.7247
0.6888	3.08	400	0.6829	0.7229
0.6471	3.85	500	0.6682	0.6802

Framework versions

• Transformers 4.38.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0