README.md

metadata

language:
  - ca
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Catalan
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 ca
          type: mozilla-foundation/common_voice_11_0
          args: 'config: ml, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 8.569471791798646

Whisper Small Catalan

This is an automatic speech recognition model that also does punctuation and casing. Vegeu projecte de millora dels models Whisper (Catalan).

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 ca dataset. It achieves the following results on the evaluation set:

• Loss: 0.1980
• Wer: 8.5695

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: 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: 500
• training_steps: 20000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2128	0.1	2000	0.2644	13.0303
0.1361	1.1	4000	0.2300	10.9568
0.0658	2.1	6000	0.2376	11.2810
0.102	3.09	8000	0.2156	9.8730
0.0706	4.09	10000	0.2126	9.6179
0.0428	5.09	12000	0.2178	9.3405
0.0503	6.09	14000	0.2109	9.1356
0.0778	7.08	16000	0.2058	9.2001
0.0082	8.08	18000	0.2173	8.9941
0.0994	9.08	20000	0.1980	8.5695

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.10.0+cu102
• Datasets 2.7.1
• Tokenizers 0.13.2