README.md

metadata

license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - common_voice_9_0
metrics:
  - wer
model-index:
  - name: cv9-special-batch12-lr4-small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_9_0
          type: common_voice_9_0
          config: id
          split: train
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 0.3947650718729886

cv9-special-batch12-lr4-small

This model is a fine-tuned version of openai/whisper-small on the common_voice_9_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0004
• Wer: 0.3948

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: 0.0001
• train_batch_size: 12
• eval_batch_size: 6
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2264	2.38	1000	0.1836	14.9989
0.0873	4.75	2000	0.0633	5.0869
0.0236	7.13	3000	0.0262	1.8086
0.0068	9.5	4000	0.0062	0.6222
0.0002	11.88	5000	0.0004	0.3948

Framework versions

• Transformers 4.31.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.13.1
• Tokenizers 0.13.3