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whisper-medium-lv-ver1
FelixK7/whisper-medium-lv-ver1
whisper-medium-lv-ver1 is a automatic speech recognition model from FelixK7. 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
- Sep 30, 2024
- Updated
- Oct 1, 2024
- SHA
- 7059e073
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. -->
Whisper medium LV - Felikss Kleins
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2416
- Wer: 11.9387
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.02 | 200 | 0.2930 | 22.3576 |
| 0.9797 | 1.0116 | 400 | 0.2359 | 18.2083 |
| 0.357 | 2.0033 | 600 | 0.2274 | 16.4665 |
| 0.2582 | 2.0233 | 800 | 0.2111 | 15.6402 |
| 0.1718 | 3.0149 | 1000 | 0.2135 | 14.9883 |
| 0.1718 | 4.0066 | 1200 | 0.2090 | 14.2294 |
| 0.1355 | 4.0266 | 1400 | 0.2193 | 13.5537 |
| 0.1024 | 5.0183 | 1600 | 0.2255 | 14.5048 |
| 0.0836 | 6.0099 | 1800 | 0.2145 | 12.9751 |
| 0.0699 | 7.0015 | 2000 | 0.2232 | 13.2129 |
| 0.0699 | 7.0216 | 2200 | 0.2181 | 12.7155 |
| 0.0598 | 8.0132 | 2400 | 0.2192 | 12.7076 |
| 0.054 | 9.0048 | 2600 | 0.2348 | 13.0048 |
| 0.0452 | 9.0249 | 2800 | 0.2241 | 13.0940 |
| 0.0433 | 10.0165 | 3000 | 0.2406 | 12.6362 |
| 0.0433 | 11.0082 | 3200 | 0.2283 | 12.5332 |
| 0.0377 | 11.0282 | 3400 | 0.2293 | 12.2201 |
| 0.0317 | 12.0198 | 3600 | 0.2323 | 12.6144 |
| 0.0297 | 13.0114 | 3800 | 0.2309 | 12.2974 |
| 0.0267 | 14.0031 | 4000 | 0.2342 | 11.9011 |
| 0.0267 | 14.0231 | 4200 | 0.2286 | 12.1171 |
| 0.0243 | 15.0147 | 4400 | 0.2364 | 12.0854 |
| 0.0218 | 16.0064 | 4600 | 0.2405 | 12.1805 |
| 0.021 | 16.0264 | 4800 | 0.2422 | 12.0338 |
| 0.0173 | 17.0180 | 5000 | 0.2416 | 11.9387 |
Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.0.1
- Datasets 3.0.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- License
- apache-2.0
- Languages
- lv
- Created
- Sep 30, 2024
- Updated
- Oct 1, 2024