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my_awesome_asr_mind_model
HuggingFaceSun/my_awesome_asr_mind_model
my_awesome_asr_mind_model is a automatic speech recognition model from HuggingFaceSun. 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 30, 2023
- Updated
- May 31, 2023
- SHA
- 6a2287d5
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. -->
my_awesome_asr_mind_model
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: 3.2641
- 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: 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
- training_steps: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 51.824 | 1.0 | 5 | 42.3534 | 1.0 |
| 48.753 | 2.0 | 10 | 42.3534 | 1.0 |
| 32.07 | 3.0 | 15 | 3.8432 | 1.0 |
| 3.7454 | 4.0 | 20 | 3.2294 | 1.0 |
| 3.2491 | 5.0 | 25 | 3.2486 | 1.0 |
| 3.1421 | 6.0 | 30 | 3.2641 | 1.0 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- May 30, 2023
- Updated
- May 31, 2023