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wav2vec2-1b-E30_freq_pause_speed
Gummybear05/wav2vec2-1b-E30_freq_pause_speed
wav2vec2-1b-E30_freq_pause_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
- Dec 3, 2024
- Updated
- Dec 3, 2024
- SHA
- dc08ec5e
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. -->
wav2vec2-1b-E30_freq_pause_speed
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5381
- Cer: 14.3033
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 50
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 9.3347 | 0.2580 | 200 | 3.0510 | 67.1170 |
| 1.6722 | 0.5160 | 400 | 1.7179 | 39.9495 |
| 1.1366 | 0.7741 | 600 | 1.4161 | 34.0343 |
| 0.9454 | 1.0321 | 800 | 1.0728 | 26.3217 |
| 0.8179 | 1.2901 | 1000 | 1.0363 | 26.1219 |
| 0.7504 | 1.5481 | 1200 | 0.9902 | 26.1748 |
| 0.676 | 1.8062 | 1400 | 0.9778 | 24.4008 |
| 0.6309 | 2.0642 | 1600 | 0.9562 | 24.5359 |
| 0.523 | 2.3222 | 1800 | 0.9541 | 24.5888 |
| 0.469 | 2.5802 | 2000 | 0.8640 | 22.1041 |
| 0.4512 | 2.8383 | 2200 | 0.7965 | 20.3595 |
| 0.3876 | 3.0963 | 2400 | 0.6971 | 18.5914 |
| 0.3249 | 3.3543 | 2600 | 0.6755 | 18.1450 |
| 0.2832 | 3.6123 | 2800 | 0.6407 | 16.8174 |
| 0.2836 | 3.8703 | 3000 | 0.6073 | 16.1125 |
| 0.2379 | 4.1284 | 3200 | 0.6392 | 16.3886 |
| 0.1937 | 4.3864 | 3400 | 0.5707 | 14.9965 |
| 0.1871 | 4.6444 | 3600 | 0.5454 | 14.7263 |
| 0.1713 | 4.9024 | 3800 | 0.5381 | 14.3033 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.3.1.post100
- Datasets 2.19.1
- Tokenizers 0.20.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Dec 3, 2024
- Updated
- Dec 3, 2024