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sew-mid-100k-librispeech-clean-100h-ft
patrickvonplaten/sew-mid-100k-librispeech-clean-100h-ft
sew-mid-100k-librispeech-clean-100h-ft is a automatic speech recognition model from patrickvonplaten. 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
- sew
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Dec 20, 2021
- SHA
- 20e4af30
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. -->
sew-mid-100k-librispeech-clean-100h-ft
This model is a fine-tuned version of asapp/sew-mid-100k on the LIBRISPEECH_ASR - CLEAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.1976
- Wer: 0.1665
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.4274 | 0.11 | 100 | 4.1419 | 1.0 |
| 2.9657 | 0.22 | 200 | 3.1203 | 1.0 |
| 2.9069 | 0.34 | 300 | 3.0107 | 1.0 |
| 2.8666 | 0.45 | 400 | 2.8960 | 1.0 |
| 1.4535 | 0.56 | 500 | 1.4062 | 0.8664 |
| 0.6821 | 0.67 | 600 | 0.5530 | 0.4930 |
| 0.4827 | 0.78 | 700 | 0.4122 | 0.3630 |
| 0.4485 | 0.9 | 800 | 0.3597 | 0.3243 |
| 0.2666 | 1.01 | 900 | 0.3104 | 0.2790 |
| 0.2378 | 1.12 | 1000 | 0.2913 | 0.2613 |
| 0.2516 | 1.23 | 1100 | 0.2702 | 0.2452 |
| 0.2456 | 1.35 | 1200 | 0.2619 | 0.2338 |
| 0.2392 | 1.46 | 1300 | 0.2466 | 0.2195 |
| 0.2117 | 1.57 | 1400 | 0.2379 | 0.2092 |
| 0.1837 | 1.68 | 1500 | 0.2295 | 0.2029 |
| 0.1757 | 1.79 | 1600 | 0.2240 | 0.1949 |
| 0.1626 | 1.91 | 1700 | 0.2195 | 0.1927 |
| 0.168 | 2.02 | 1800 | 0.2137 | 0.1853 |
| 0.168 | 2.13 | 1900 | 0.2123 | 0.1839 |
| 0.1576 | 2.24 | 2000 | 0.2095 | 0.1803 |
| 0.1756 | 2.35 | 2100 | 0.2075 | 0.1776 |
| 0.1467 | 2.47 | 2200 | 0.2049 | 0.1754 |
| 0.1702 | 2.58 | 2300 | 0.2013 | 0.1722 |
| 0.177 | 2.69 | 2400 | 0.1993 | 0.1701 |
| 0.1417 | 2.8 | 2500 | 0.1983 | 0.1688 |
| 0.1302 | 2.91 | 2600 | 0.1977 | 0.1678 |
Framework versions
- Transformers 4.12.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.13.4.dev0
- Tokenizers 0.10.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- sew
- License
- apache-2.0
- Created
- Mar 2, 2022
- Updated
- Dec 20, 2021