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vast_base
whitebemail/vast_base
vast_base is a machine learning model from whitebemail. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Nov 21, 2024
- Updated
- Nov 21, 2024
- SHA
- ef880075
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. -->
vast_base
This model is a fine-tuned version of facebook/wav2vec2-base on the timit_asr dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.3597
- eval_cer: 0.1249
- eval_runtime: 16.6098
- eval_samples_per_second: 50.573
- eval_steps_per_second: 6.322
- epoch: 9.64
- step: 2400
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.17.0
- Pytorch 2.4.0
- Datasets 1.18.3
- Tokenizers 0.20.3
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Nov 21, 2024
- Updated
- Nov 21, 2024