Downloads · 30 days
4
5% of all-time downloads
wav2vec2-E_
Gummybear05/wav2vec2-E_
wav2vec2-E_ 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. --
All-time downloads
87
Public
Parameters
317M
30.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Dec 4, 2024
- Updated
- Dec 4, 2024
- SHA
- cfe45dde
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-E_
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: 0.7138
- Cer: 15.1116
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 |
|---|---|---|---|---|
| 29.9637 | 0.1289 | 200 | 4.9791 | 100.0 |
| 4.6123 | 0.2579 | 400 | 4.6053 | 100.0 |
| 4.546 | 0.3868 | 600 | 4.5594 | 97.9671 |
| 4.49 | 0.5158 | 800 | 4.5282 | 97.9671 |
| 4.4469 | 0.6447 | 1000 | 4.4909 | 97.9671 |
| 4.3231 | 0.7737 | 1200 | 4.3157 | 89.9412 |
| 3.7783 | 0.9026 | 1400 | 3.3710 | 58.4195 |
| 2.7113 | 1.0316 | 1600 | 2.4292 | 42.7321 |
| 2.0971 | 1.1605 | 1800 | 2.0556 | 38.2197 |
| 1.7684 | 1.2895 | 2000 | 1.6070 | 29.8472 |
| 1.5046 | 1.4184 | 2200 | 1.4542 | 27.2268 |
| 1.3672 | 1.5474 | 2400 | 1.2693 | 24.2656 |
| 1.2279 | 1.6763 | 2600 | 1.1761 | 23.5253 |
| 1.1456 | 1.8053 | 2800 | 1.0789 | 21.2338 |
| 1.0516 | 1.9342 | 3000 | 0.9792 | 19.9471 |
| 0.9609 | 2.0632 | 3200 | 0.9519 | 19.6592 |
| 0.8758 | 2.1921 | 3400 | 0.8677 | 18.0082 |
| 0.8289 | 2.3211 | 3600 | 0.8783 | 18.0082 |
| 0.783 | 2.4500 | 3800 | 0.7990 | 17.0682 |
| 0.7719 | 2.5790 | 4000 | 0.7492 | 15.7168 |
| 0.748 | 2.7079 | 4200 | 0.7483 | 16.0400 |
| 0.7377 | 2.8369 | 4400 | 0.7291 | 15.4877 |
| 0.7188 | 2.9658 | 4600 | 0.7138 | 15.1116 |
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 4, 2024
- Updated
- Dec 4, 2024