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whisper-large-v2-es
Jack200133/whisper-large-v2-es
whisper-large-v2-es is a automatic speech recognition model from Jack200133. 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
- whisper
- Access
- Public
- Created
- Sep 1, 2023
- Updated
- Sep 18, 2023
- SHA
- 4c39a7aa
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-large-v2-es
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2930
- Wer: 31.3542
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: 8
- eval_batch_size: 8
- 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: 200
- training_steps: 6000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0328 | 0.16 | 250 | 0.3149 | 26.25 |
| 0.0498 | 0.33 | 500 | 0.2925 | 37.9167 |
| 0.0666 | 0.49 | 750 | 0.2762 | 28.3333 |
| 0.0909 | 0.65 | 1000 | 0.2705 | 32.1875 |
| 0.0843 | 0.82 | 1250 | 0.2566 | 27.7083 |
| 0.1277 | 0.98 | 1500 | 0.2609 | 29.7917 |
| 0.0431 | 1.14 | 1750 | 0.2667 | 30.6250 |
| 0.0321 | 1.31 | 2000 | 0.2570 | 30.8333 |
| 0.0301 | 1.47 | 2250 | 0.2793 | 31.1458 |
| 0.0364 | 1.63 | 2500 | 0.2769 | 29.375 |
| 0.0303 | 1.8 | 2750 | 0.2755 | 28.6458 |
| 0.0226 | 1.96 | 3000 | 0.2846 | 27.9167 |
| 0.0185 | 2.12 | 3250 | 0.2863 | 26.9792 |
| 0.0161 | 2.29 | 3500 | 0.2902 | 27.8125 |
| 0.0165 | 2.45 | 3750 | 0.2903 | 32.7083 |
| 0.0145 | 2.61 | 4000 | 0.2903 | 29.8958 |
| 0.0123 | 2.78 | 4250 | 0.3076 | 27.8125 |
| 0.0129 | 2.94 | 4500 | 0.3019 | 28.4375 |
| 0.0145 | 3.1 | 4750 | 0.2917 | 26.5625 |
| 0.0118 | 3.27 | 5000 | 0.2953 | 33.6458 |
| 0.0099 | 3.43 | 5250 | 0.2881 | 33.0208 |
| 0.0088 | 3.59 | 5500 | 0.2922 | 31.5625 |
| 0.0118 | 3.76 | 5750 | 0.2935 | 30.5208 |
| 0.0103 | 3.92 | 6000 | 0.2930 | 31.3542 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- whisper
- Created
- Sep 1, 2023
- Updated
- Sep 18, 2023