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test1000v2
minjibi/test1000v2
test1000v2 is a automatic speech recognition model from minjibi. 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
- Oct 5, 2022
- Updated
- Oct 5, 2022
- SHA
- c68c035b
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. -->
test1000v2
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7873
- Wer: 0.6162
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: 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: 500
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 7.7913 | 3.22 | 100 | 3.3481 | 1.0 |
| 3.3831 | 6.44 | 200 | 3.3229 | 1.0 |
| 3.3778 | 9.67 | 300 | 3.3211 | 1.0 |
| 3.3671 | 12.89 | 400 | 3.2973 | 1.0 |
| 3.3528 | 16.13 | 500 | 3.1349 | 1.0 |
| 1.8611 | 19.35 | 600 | 0.7873 | 0.6162 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.10.0+cu102
- Datasets 1.4.1
- Tokenizers 0.12.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Oct 5, 2022
- Updated
- Oct 5, 2022