README.md

metadata

language:
  - pt
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
base_model: openai/whisper-tiny
model-index:
  - name: Whisper Tiny PT with Common Voice 11
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          args: 'config: pt, split: test'
        metrics:
          - type: wer
            value: 33.24473522796974
            name: Wer

Whisper Tiny PT with Common Voice 11

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5205
• Wer: 33.2447

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: 8
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 16000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.3154	0.44	1000	0.4987	36.2196
0.3252	0.88	2000	0.4586	33.6213
0.1989	1.32	3000	0.4457	32.7455
0.3112	1.76	4000	0.4356	31.4097
0.1329	2.2	5000	0.4348	31.1559
0.1193	2.64	6000	0.4343	31.4046
0.0723	3.07	7000	0.4424	31.5869
0.0698	3.51	8000	0.4497	32.0827
0.0865	3.95	9000	0.4497	31.0945
0.0522	4.39	10000	0.4716	32.2190
0.0542	4.83	11000	0.4761	32.6944
0.061	5.27	12000	0.4983	32.0691
0.0459	5.71	13000	0.4985	32.4968
0.0338	6.15	14000	0.5123	33.3129
0.0492	6.59	15000	0.5217	33.2686
0.0194	7.03	16000	0.5205	33.2447

Framework versions

• Transformers 4.25.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.6.1
• Tokenizers 0.13.1