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model-1h
ebonazza2910/model-1h
model-1h is a automatic speech recognition model from ebonazza2910. 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
- May 10, 2022
- Updated
- May 10, 2022
- SHA
- fef7a26e
Datasets
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. -->
model-1h
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 1.8317
- Wer: 1.0
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 11.4106 | 1.24 | 10 | 7.1597 | 1.0 |
| 4.777 | 2.47 | 20 | 3.9782 | 1.0 |
| 3.6585 | 3.71 | 30 | 3.3961 | 1.0 |
| 3.3143 | 4.94 | 40 | 3.1481 | 1.0 |
| 3.3318 | 6.24 | 50 | 3.0596 | 1.0 |
| 3.1368 | 7.47 | 60 | 2.9751 | 1.0 |
| 3.1058 | 8.71 | 70 | 2.9510 | 1.0 |
| 3.0605 | 9.94 | 80 | 2.9479 | 1.0 |
| 3.2043 | 11.24 | 90 | 2.9270 | 1.0 |
| 3.0424 | 12.47 | 100 | 2.9349 | 1.0 |
| 3.0374 | 13.71 | 110 | 2.9316 | 1.0 |
| 3.0256 | 14.94 | 120 | 2.9165 | 1.0 |
| 3.1724 | 16.24 | 130 | 2.9076 | 1.0 |
| 3.0119 | 17.47 | 140 | 2.9034 | 1.0 |
| 2.9937 | 18.71 | 150 | 2.8812 | 1.0 |
| 2.9775 | 19.94 | 160 | 2.8674 | 1.0 |
| 3.0826 | 21.24 | 170 | 2.8147 | 1.0 |
| 2.8717 | 22.47 | 180 | 2.7212 | 1.0 |
| 2.7714 | 23.71 | 190 | 2.6149 | 0.9952 |
| 2.634 | 24.94 | 200 | 2.4611 | 0.9984 |
| 2.5637 | 26.24 | 210 | 2.2734 | 1.0 |
| 2.237 | 27.47 | 220 | 2.0705 | 1.0 |
| 2.0381 | 28.71 | 230 | 1.9216 | 1.0 |
| 1.8788 | 29.94 | 240 | 1.8317 | 1.0 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.1+cu102
- Datasets 1.18.3
- Tokenizers 0.10.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- May 10, 2022
- Updated
- May 10, 2022