Downloads · 30 days
6
8% of all-time downloads
wav2vec2-base_toy_train_data_fast_10pct
scasutt/wav2vec2-base_toy_train_data_fast_10pct
wav2vec2-base_toy_train_data_fast_10pct is a automatic speech recognition model from scasutt. 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
71
Public
Repo size
4.2 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin378 MB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 26, 2022
- Updated
- Mar 26, 2022
- SHA
- a1d1b674
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-base_toy_train_data_fast_10pct
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3087
- Wer: 0.7175
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
- gradient_accumulation_steps: 2
- 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: 1000
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.1309 | 1.05 | 250 | 3.4541 | 0.9982 |
| 3.0499 | 2.1 | 500 | 3.0231 | 0.9982 |
| 1.4839 | 3.15 | 750 | 1.4387 | 0.9257 |
| 1.1697 | 4.2 | 1000 | 1.3729 | 0.8792 |
| 0.9353 | 5.25 | 1250 | 1.2608 | 0.8445 |
| 0.7298 | 6.3 | 1500 | 1.1867 | 0.8052 |
| 0.6418 | 7.35 | 1750 | 1.2414 | 0.7997 |
| 0.5698 | 8.4 | 2000 | 1.2240 | 0.7766 |
| 0.5084 | 9.45 | 2250 | 1.1910 | 0.7687 |
| 0.4912 | 10.5 | 2500 | 1.2241 | 0.7617 |
| 0.4144 | 11.55 | 2750 | 1.2412 | 0.7477 |
| 0.4153 | 12.6 | 3000 | 1.2736 | 0.7511 |
| 0.405 | 13.65 | 3250 | 1.2827 | 0.7328 |
| 0.3852 | 14.7 | 3500 | 1.1981 | 0.7331 |
| 0.3829 | 15.75 | 3750 | 1.3035 | 0.7347 |
| 0.3538 | 16.81 | 4000 | 1.3003 | 0.7240 |
| 0.3385 | 17.86 | 4250 | 1.3354 | 0.7304 |
| 0.3108 | 18.91 | 4500 | 1.2983 | 0.7229 |
| 0.3037 | 19.96 | 4750 | 1.3087 | 0.7175 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.11.0+cu102
- Datasets 2.0.0
- Tokenizers 0.11.6
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 26, 2022
- Updated
- Mar 26, 2022