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fineturning
Aviral2412/fineturning
fineturning is a automatic speech recognition model from Aviral2412. 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
- Access
- Public
- Created
- Apr 15, 2024
- Updated
- Apr 15, 2024
- SHA
- 8f9ad860
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. -->
fineturning
This model is a fine-tuned version of Aviral2412/mini_model on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7515
- Wer: 1.0
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: 0.0001
- train_batch_size: 8
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.4377 | 21.74 | 500 | 2.7515 | 1.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 1.18.3
- Tokenizers 0.15.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- Created
- Apr 15, 2024
- Updated
- Apr 15, 2024