README.md

metadata

language:
  - bg
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: openai/whisper-small-finetuned-common_voice_13_0-bg
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0
          type: mozilla-foundation/common_voice_13_0
          config: bg
          split: test
          args: bg
        metrics:
          - name: Wer
            type: wer
            value: 23.264792642720806

openai/whisper-small-finetuned-common_voice_13_0-bg

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3983
• Wer Ortho: 30.2504
• Wer: 23.2648

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0787	2.78	500	0.3445	31.2999	24.2365
0.0145	5.56	1000	0.3983	30.2504	23.2648

Framework versions

• Transformers 4.36.2
• Pytorch 1.12.0+cu102
• Datasets 2.15.0
• Tokenizers 0.15.0