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wav2vec2-bert-CV16-en-libri
ylacombe/wav2vec2-bert-CV16-en-libri
wav2vec2-bert-CV16-en-libri is a automatic speech recognition model from ylacombe. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- mit
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Jan 16, 2024
- Updated
- Jan 23, 2024
- SHA
- df5885a3
Base models
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. -->
wav2vec2-bert-CV16-en-libri
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the LIBRISPEECH_ASR - CLEAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.1035
- Wer: 0.0708
- Cer: 0.0194
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: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 72
- total_eval_batch_size: 36
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 7.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|---|---|---|---|---|---|
| 2.8812 | 0.63 | 250 | 1.0000 | 2.8923 | 1.0 |
| 1.2899 | 1.26 | 500 | 0.2563 | 1.1471 | 0.7030 |
| 0.5276 | 1.89 | 750 | 0.1127 | 0.4687 | 0.4114 |
| 0.3313 | 2.52 | 1000 | 0.0659 | 0.2870 | 0.2577 |
| 0.2089 | 3.16 | 1250 | 0.0445 | 0.2079 | 0.1766 |
| 0.1634 | 3.79 | 1500 | 0.0366 | 0.1687 | 0.1411 |
| 0.1546 | 4.42 | 1750 | 0.1452 | 0.1138 | 0.0294 |
| 0.1245 | 5.05 | 2000 | 0.1316 | 0.0973 | 0.0260 |
| 0.1341 | 5.68 | 2250 | 0.1196 | 0.0867 | 0.0234 |
| 0.0942 | 6.31 | 2500 | 0.1128 | 0.0794 | 0.0213 |
| 0.0848 | 6.94 | 2750 | 0.1077 | 0.0717 | 0.0197 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- License
- mit
- Created
- Jan 16, 2024
- Updated
- Jan 23, 2024