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wav2vec2-base_toy_train_data_masked_audio_10ms
scasutt/wav2vec2-base_toy_train_data_masked_audio_10ms
wav2vec2-base_toy_train_data_masked_audio_10ms 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. --
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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
- 36f58545
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_masked_audio_10ms
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: 1.2477
- Wer: 0.7145
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 |
|---|---|---|---|---|
| 3.1337 | 1.05 | 250 | 3.4081 | 0.9982 |
| 3.0792 | 2.1 | 500 | 3.2446 | 0.9982 |
| 2.0577 | 3.15 | 750 | 1.5839 | 0.9492 |
| 1.3639 | 4.2 | 1000 | 1.3279 | 0.8798 |
| 1.0814 | 5.25 | 1250 | 1.1629 | 0.8294 |
| 0.8722 | 6.3 | 1500 | 1.1305 | 0.8140 |
| 0.7602 | 7.35 | 1750 | 1.1241 | 0.7972 |
| 0.6982 | 8.4 | 2000 | 1.1429 | 0.7780 |
| 0.6494 | 9.45 | 2250 | 1.1047 | 0.7620 |
| 0.5924 | 10.5 | 2500 | 1.1756 | 0.7649 |
| 0.5385 | 11.55 | 2750 | 1.2230 | 0.7736 |
| 0.5026 | 12.6 | 3000 | 1.1783 | 0.7472 |
| 0.4973 | 13.65 | 3250 | 1.1613 | 0.7287 |
| 0.4726 | 14.7 | 3500 | 1.1923 | 0.7345 |
| 0.4521 | 15.75 | 3750 | 1.2153 | 0.7171 |
| 0.4552 | 16.81 | 4000 | 1.2485 | 0.7226 |
| 0.422 | 17.86 | 4250 | 1.2664 | 0.7240 |
| 0.3708 | 18.91 | 4500 | 1.2352 | 0.7148 |
| 0.3516 | 19.96 | 4750 | 1.2477 | 0.7145 |
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