Downloads · 30 days
5
19% of all-time downloads
wav2vec2-E50_freq_speed
Gummybear05/wav2vec2-E50_freq_speed
wav2vec2-E50_freq_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. --
All-time downloads
26
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
- Oct 20, 2024
- Updated
- Oct 20, 2024
- SHA
- 1fda6b76
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_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: 1.2867
- Cer: 26.4509
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 |
|---|---|---|---|---|
| 36.1912 | 0.1289 | 200 | 4.9281 | 100.0 |
| 4.8744 | 0.2579 | 400 | 4.6344 | 100.0 |
| 4.7389 | 0.3868 | 600 | 4.6396 | 100.0 |
| 4.7053 | 0.5158 | 800 | 4.6142 | 100.0 |
| 4.6271 | 0.6447 | 1000 | 4.5886 | 98.9779 |
| 4.5325 | 0.7737 | 1200 | 4.3545 | 97.4213 |
| 4.0987 | 0.9026 | 1400 | 3.3740 | 62.2768 |
| 3.1619 | 1.0316 | 1600 | 2.8281 | 48.0733 |
| 2.8074 | 1.1605 | 1800 | 2.4434 | 44.3257 |
| 2.5099 | 1.2895 | 2000 | 2.2456 | 40.7542 |
| 2.3202 | 1.4184 | 2200 | 2.0216 | 38.0169 |
| 2.2438 | 1.5474 | 2400 | 1.8903 | 35.2796 |
| 2.0245 | 1.6763 | 2600 | 1.8335 | 34.7098 |
| 1.9285 | 1.8053 | 2800 | 1.7468 | 34.4690 |
| 1.83 | 1.9342 | 3000 | 1.5999 | 31.0503 |
| 1.6842 | 2.0632 | 3200 | 1.5379 | 30.3454 |
| 1.5576 | 2.1921 | 3400 | 1.4967 | 29.8755 |
| 1.4787 | 2.3211 | 3600 | 1.3937 | 28.0721 |
| 1.458 | 2.4500 | 3800 | 1.3861 | 27.7079 |
| 1.3927 | 2.5790 | 4000 | 1.2945 | 26.1631 |
| 1.3578 | 2.7079 | 4200 | 1.3155 | 27.2968 |
| 1.3148 | 2.8369 | 4400 | 1.2744 | 26.1454 |
| 1.3245 | 2.9658 | 4600 | 1.2867 | 26.4509 |
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