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wav2vec2-base-splitted-idrak-exp_test
m-aliabbas/wav2vec2-base-splitted-idrak-exp_test
wav2vec2-base-splitted-idrak-exp_test is a automatic speech recognition model from m-aliabbas. 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
- Dec 2, 2022
- Updated
- Dec 2, 2022
- SHA
- 763010b8
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-splitted-idrak-exp_test
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: 3.6360
- 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: 0.001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.4894 | 25.0 | 100 | 3.3342 | 1.0 |
| 3.3573 | 50.0 | 200 | 3.5575 | 1.0 |
| 3.331 | 75.0 | 300 | 3.5871 | 1.0 |
| 3.3274 | 100.0 | 400 | 3.6360 | 1.0 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu116
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Dec 2, 2022
- Updated
- Dec 2, 2022