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wav2vec2-E50_freq_
Gummybear05/wav2vec2-E50_freq_
wav2vec2-E50_freq_ is a automatic speech recognition model from Gummybear05. 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
- wav2vec2
- Access
- Public
- Created
- Dec 5, 2024
- Updated
- Dec 5, 2024
- SHA
- f7e7b2a9
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. -->
wav2vec2-E50_freq_
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8668
- Cer: 19.9765
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: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 35.2248 | 0.1289 | 200 | 5.2165 | 100.0 |
| 4.8505 | 0.2579 | 400 | 4.6730 | 100.0 |
| 4.7409 | 0.3868 | 600 | 4.6010 | 100.0 |
| 4.7179 | 0.5158 | 800 | 4.5777 | 100.0 |
| 4.6385 | 0.6447 | 1000 | 4.5493 | 100.0 |
| 4.474 | 0.7737 | 1200 | 4.3678 | 95.6287 |
| 3.613 | 0.9026 | 1400 | 3.0539 | 52.1915 |
| 2.673 | 1.0316 | 1600 | 2.3161 | 41.9976 |
| 2.296 | 1.1605 | 1800 | 1.9627 | 37.4031 |
| 2.0153 | 1.2895 | 2000 | 1.8249 | 34.2597 |
| 1.8806 | 1.4184 | 2200 | 1.6718 | 32.1445 |
| 1.7151 | 1.5474 | 2400 | 1.4662 | 30.1175 |
| 1.5519 | 1.6763 | 2600 | 1.4178 | 29.8472 |
| 1.4466 | 1.8053 | 2800 | 1.2471 | 26.9330 |
| 1.3414 | 1.9342 | 3000 | 1.1782 | 24.7885 |
| 1.2326 | 2.0632 | 3200 | 1.1008 | 23.8425 |
| 1.1417 | 2.1921 | 3400 | 1.1546 | 25.1586 |
| 1.0752 | 2.3211 | 3600 | 1.0035 | 22.0035 |
| 1.0329 | 2.4500 | 3800 | 0.9728 | 21.5394 |
| 1.0197 | 2.5790 | 4000 | 0.9201 | 20.8284 |
| 0.9868 | 2.7079 | 4200 | 0.9076 | 20.2350 |
| 0.944 | 2.8369 | 4400 | 0.8786 | 19.8120 |
| 0.9381 | 2.9658 | 4600 | 0.8668 | 19.9765 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Dec 5, 2024
- Updated
- Dec 5, 2024