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parp-wave2vec
atishayj25/parp-wave2vec
parp-wave2vec is a automatic speech recognition model from atishayj25. 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
- Apr 27, 2024
- Updated
- May 4, 2024
- SHA
- e89d93e7
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. -->
parp-wave2vec
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: 0.4483
- Wer: 0.3476
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: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.2839 | 1.59 | 100 | 5.8388 | 1.0 |
| 3.3061 | 3.17 | 200 | 3.2376 | 1.0 |
| 2.991 | 4.76 | 300 | 3.0763 | 1.0 |
| 2.9309 | 6.35 | 400 | 2.9807 | 1.0 |
| 2.8255 | 7.94 | 500 | 2.7915 | 1.0 |
| 2.4385 | 9.52 | 600 | 2.0330 | 1.0139 |
| 1.6806 | 11.11 | 700 | 1.0553 | 0.8019 |
| 0.7871 | 12.7 | 800 | 0.5798 | 0.5345 |
| 0.423 | 14.29 | 900 | 0.4795 | 0.4583 |
| 0.2885 | 15.87 | 1000 | 0.4599 | 0.4204 |
| 0.2297 | 17.46 | 1100 | 0.4404 | 0.3953 |
| 0.1869 | 19.05 | 1200 | 0.4463 | 0.3857 |
| 0.1478 | 20.63 | 1300 | 0.4319 | 0.3751 |
| 0.1386 | 22.22 | 1400 | 0.4364 | 0.3715 |
| 0.1158 | 23.81 | 1500 | 0.4448 | 0.3652 |
| 0.1076 | 25.4 | 1600 | 0.4324 | 0.3528 |
| 0.098 | 26.98 | 1700 | 0.4406 | 0.3607 |
| 0.0933 | 28.57 | 1800 | 0.4367 | 0.3547 |
| 0.0848 | 30.16 | 1900 | 0.4341 | 0.3526 |
| 0.0773 | 31.75 | 2000 | 0.4330 | 0.3550 |
| 0.0721 | 33.33 | 2100 | 0.4418 | 0.3493 |
| 0.0716 | 34.92 | 2200 | 0.4379 | 0.3494 |
| 0.067 | 36.51 | 2300 | 0.4369 | 0.3497 |
| 0.064 | 38.1 | 2400 | 0.4494 | 0.3488 |
| 0.06 | 39.68 | 2500 | 0.4483 | 0.3476 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Apr 27, 2024
- Updated
- May 4, 2024