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w2v-fine-tune-test-no-punct4
web2savar/w2v-fine-tune-test-no-punct4
w2v-fine-tune-test-no-punct4 is a automatic speech recognition model from web2savar. 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
- wav2vec2-bert
- Access
- Public
- Created
- Jan 24, 2024
- Updated
- Jan 24, 2024
- SHA
- 0e40e2f5
Base models
Datasets
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. -->
w2v-fine-tune-test-no-punct4
This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the common_voice_16_0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0213
- Wer: 0.888
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: 5e-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: 20
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.5721 | 1.54 | 20 | 3.5316 | 1.0 |
| 3.3513 | 3.08 | 40 | 3.3113 | 1.0 |
| 2.9765 | 4.62 | 60 | 3.1604 | 1.016 |
| 2.0468 | 6.15 | 80 | 2.5162 | 1.02 |
| 0.8977 | 7.69 | 100 | 1.4944 | 1.008 |
| 0.3831 | 9.23 | 120 | 1.0213 | 0.888 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- Created
- Jan 24, 2024
- Updated
- Jan 24, 2024