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whisper-medium-mix-fr
deepdml/whisper-medium-mix-fr
whisper-medium-mix-fr is a automatic speech recognition model from deepdml. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- whisper
- Access
- Public
- Created
- Dec 13, 2022
- Updated
- Dec 15, 2022
- SHA
- 28edaa53
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
deepdml/whisper-medium-mix-fr
This model is a fine-tuned version of deepdml/whisper-medium-mix-fr on the mozilla-foundation/common_voice_11_0, google/fleurs, facebook/multilingual_librispeech and facebook/voxpopuli datasets. It achieves the following results on the evaluation set:
- Loss: 0.2599
- Wer: 11.2278
Using the evalutaion script provided in the Whisper Sprint the model achieves these results on the test sets (WER):
- google/fleurs: 9.3526 %
(python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="google/fleurs" --config="fr_fr" --device=0 --language="fr") - facebook/multilingual_librispeech: 6.3468 %
(python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="facebook/multilingual_librispeech" --config="french" --device=0 --language="fr") - facebook/voxpopuli: 10.0653 %
(python run_eval_whisper_streaming.py --model_id="deepdml/whisper-medium-mix-fr" --dataset="facebook/voxpopuli" --config="fr" --device=0 --language="fr")
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
Training data used:
- mozilla-foundation/common_voice_11_0: fr, train+validation
- google/fleurs: fr_fr, train
- facebook/multilingual_librispeech: french, train
- facebook/voxpopuli: fr, train
Evaluating over test split from mozilla-foundation/common_voice_11_0 dataset.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0855 | 0.25 | 1000 | 0.2826 | 12.4230 |
| 0.0569 | 0.5 | 2000 | 0.2768 | 11.9577 |
| 0.0724 | 0.75 | 3000 | 0.2670 | 11.6106 |
| 0.069 | 1.0 | 4000 | 0.2599 | 11.2278 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- Languages
- fr
- Created
- Dec 13, 2022
- Updated
- Dec 15, 2022