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wav2vec2-large-asr-th-4-gram
DylanonWic/wav2vec2-large-asr-th-4-gram
wav2vec2-large-asr-th-4-gram is a automatic speech recognition model from DylanonWic. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 27, 2023
- Updated
- Jul 27, 2023
- SHA
- 6e9eb5ea
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-large-asr-th-2
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.1819
- eval_wer: 0.3346
- eval_cer: 0.0910
- eval_runtime: 735.0436
- eval_samples_per_second: 13.822
- eval_steps_per_second: 1.728
- epoch: 0.95
- step: 4000
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- Languages
- th
- Created
- Mar 27, 2023
- Updated
- Jul 27, 2023