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whisper-base-en
CheeLi03/whisper-base-en
whisper-base-en is a machine learning model from CheeLi03. 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
- Oct 15, 2024
- Updated
- Oct 15, 2024
- SHA
- cd9d0c41
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 Base English - Chee Li
This model is a fine-tuned version of openai/whisper-base on the Google Fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.5048
- Wer: 13.9152
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: 1e-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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0182 | 5.3191 | 1000 | 0.4233 | 15.7209 |
| 0.0018 | 10.6383 | 2000 | 0.4743 | 13.7061 |
| 0.001 | 15.9574 | 3000 | 0.4963 | 13.6433 |
| 0.0008 | 21.2766 | 4000 | 0.5048 | 13.9152 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- whisper
- License
- apache-2.0
- Languages
- en
- Created
- Oct 15, 2024
- Updated
- Oct 15, 2024