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whisper-medium-sanskrit-try-2
Bidwill/whisper-medium-sanskrit-try-2
whisper-medium-sanskrit-try-2 is a automatic speech recognition model from Bidwill. Use it when you need speech turned into text. It is set up for transformers. 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
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- whisper
- Access
- Public
- Created
- Oct 22, 2023
- Updated
- Oct 30, 2023
- SHA
- 689eb5e2
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 medium sanskrit try - Bidit Sadhukhan
This model is a fine-tuned version of openai/whisper-Medium on the load_data dataset. It achieves the following results on the evaluation set:
- Loss: 0.1326
- Wer: 24.8767
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: 6.25e-06
- 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: reduce_lr_on_plateau
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0708 | 0.23 | 500 | 0.1239 | 35.9144 |
| 0.0516 | 0.47 | 1000 | 0.1093 | 31.4377 |
| 0.0492 | 0.7 | 1500 | 0.1031 | 28.9836 |
| 0.0472 | 0.93 | 2000 | 0.1003 | 27.9471 |
| 0.027 | 1.17 | 2500 | 0.1078 | 27.6726 |
| 0.0246 | 1.4 | 3000 | 0.0959 | 25.6948 |
| 0.0286 | 1.63 | 3500 | 0.1000 | 25.3138 |
| 0.0235 | 1.86 | 4000 | 0.0980 | 25.1513 |
| 0.0113 | 2.1 | 4500 | 0.1035 | 24.4453 |
| 0.017 | 2.33 | 5000 | 0.1038 | 25.0896 |
| 0.0171 | 2.56 | 5500 | 0.1038 | 25.1121 |
| 0.017 | 2.8 | 6000 | 0.1105 | 25.5603 |
| 0.0065 | 3.03 | 6500 | 0.1182 | 25.4370 |
| 0.0078 | 3.26 | 7000 | 0.1247 | 25.2409 |
| 0.0111 | 3.5 | 7500 | 0.1304 | 26.5464 |
| 0.0102 | 3.73 | 8000 | 0.1191 | 25.8909 |
| 0.0155 | 3.96 | 8500 | 0.1142 | 25.2073 |
| 0.006 | 4.2 | 9000 | 0.1269 | 24.9496 |
| 0.0074 | 4.43 | 9500 | 0.1335 | 25.1513 |
| 0.0053 | 4.66 | 10000 | 0.1326 | 24.8767 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Created
- Oct 22, 2023
- Updated
- Oct 30, 2023