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whisper-finetuned-base
idaracecilia/whisper-finetuned-base
whisper-finetuned-base is a machine learning model from idaracecilia. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Aug 14, 2024
- Updated
- Aug 14, 2024
- SHA
- cb9f0e6d
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. -->
Whisper Fine tuned Base
This model is a fine-tuned version of openai/whisper-base.en on the Fyp Dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.3550
- Wer: 15.0186
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: 5
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3123 | 0.5 | 25 | 0.4652 | 20.1147 |
| 0.3282 | 1.0 | 50 | 0.3655 | 16.2673 |
| 0.0376 | 1.5 | 75 | 0.3693 | 15.4573 |
| 0.0468 | 2.0 | 100 | 0.3754 | 20.2497 |
| 0.0067 | 2.5 | 125 | 0.3585 | 15.3898 |
| 0.0098 | 3.0 | 150 | 0.3550 | 15.0186 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Type
- whisper
- License
- apache-2.0
- Languages
- eng
- Created
- Aug 14, 2024
- Updated
- Aug 14, 2024