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wav2vec2-E30_speed
Gummybear05/wav2vec2-E30_speed
wav2vec2-E30_speed 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
- Oct 20, 2024
- Updated
- Oct 20, 2024
- SHA
- 26329c32
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-E30_speed
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: 1.5403
- Cer: 30.0576
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|
| 38.4014 | 0.1289 | 200 | 5.0924 | 100.0 |
| 4.967 | 0.2579 | 400 | 4.7266 | 100.0 |
| 4.803 | 0.3868 | 600 | 4.6563 | 100.0 |
| 4.7976 | 0.5158 | 800 | 4.7264 | 100.0 |
| 4.7401 | 0.6447 | 1000 | 4.6214 | 100.0 |
| 4.7227 | 0.7737 | 1200 | 4.6575 | 100.0 |
| 4.6903 | 0.9026 | 1400 | 4.6785 | 100.0 |
| 4.5596 | 1.0316 | 1600 | 4.4755 | 100.0 |
| 4.3655 | 1.1605 | 1800 | 4.1150 | 90.4312 |
| 3.7719 | 1.2895 | 2000 | 3.5459 | 66.0186 |
| 3.2218 | 1.4184 | 2200 | 2.9444 | 54.4643 |
| 2.9251 | 1.5474 | 2400 | 2.7016 | 50.6344 |
| 2.6652 | 1.6763 | 2600 | 2.5111 | 45.5416 |
| 2.4444 | 1.8053 | 2800 | 2.2185 | 40.9246 |
| 2.2701 | 1.9342 | 3000 | 2.0419 | 38.7101 |
| 2.1017 | 2.0632 | 3200 | 1.9275 | 36.5836 |
| 1.982 | 2.1921 | 3400 | 1.9218 | 36.9302 |
| 1.8856 | 2.3211 | 3600 | 1.7415 | 33.2648 |
| 1.7977 | 2.4500 | 3800 | 1.7043 | 33.2942 |
| 1.7146 | 2.5790 | 4000 | 1.6084 | 30.8036 |
| 1.6798 | 2.7079 | 4200 | 1.5947 | 31.0033 |
| 1.6234 | 2.8369 | 4400 | 1.5576 | 30.2573 |
| 1.6289 | 2.9658 | 4600 | 1.5403 | 30.0576 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Oct 20, 2024
- Updated
- Oct 20, 2024