README.md

metadata

language:
  - en
license: apache-2.0
base_model: futureProofGlitch/whisper-small
tags:
  - generated_from_trainer
datasets:
  - speechcolab/gigaspeech
metrics:
  - wer
model-index:
  - name: FutureProofGlitch - Whisper Small - Version 2.0
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Gigaspeech
          type: speechcolab/gigaspeech
          config: xs
          split: test
          args: xs
        metrics:
          - name: Wer
            type: wer
            value: 16.45244089773603

FutureProofGlitch - Whisper Small - Version 2.0

This model is a fine-tuned version of futureProofGlitch/whisper-small on the Gigaspeech dataset. It achieves the following results on the evaluation set:

• Loss: 0.3078
• Wer Ortho: 28.4362
• Wer: 16.4524

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: 1.5e-05
• train_batch_size: 16
• eval_batch_size: 16
• 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
0.2267	0.5	500	0.3309	29.5720	18.0966
0.2035	0.99	1000	0.3078	28.4362	16.4524

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2