Comments (2)
ycmin95
commented on August 23, 2024
@chenzekang
We conduct experiments on three TITAN XP (12GB * 3) GPUs, and each end-to-end training takes about 40 hours for 80 epochs. There is no special need for RAM, our server has 64 GB RAM.
You can also conduct precursor experiments on framewise features (which can be extracted with the provided pretrained model under the features mode), which can accelerate the training process. However, this experiment setting can only be used for tuning the alignment module.
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chenzekang
commented on August 23, 2024
谢谢，非常感谢您的回复
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Related Issues (20)
- Error when i run the training part main.py HOT 1
- unable to run successfully when I run main.py HOT 1
- unable to successfully install CTC HOT 5
- Detailed code running steps HOT 19
- Visualizing the predicted alignments HOT 1
- unable to run these repository on google colab HOT 1
- Data augmention error HOT 4
- about the feature extractor architecture HOT 6
- Successfully inference, but unable to train HOT 3
- Visualize Epoch vs Loss HOT 1
- Hardware and Software Specifications for this research. HOT 3
- Gloss Segment Boundary Assignment Algorithm (GSBA) HOT 1
- Does your PHOENIX-2014-T dataset have /1/ folder? HOT 1
- model or model.parameters()? HOT 2
- Does your model produce different results each time it is run? HOT 4
- Training the baseline (without VAC, SMKD) HOT 2
- How can I use a trained model to test a video? HOT 1
- unable to reconize any word but the loss is decreasing??? HOT 1
- Does preprocess.sh have an effect if using datasets other than phoneix? HOT 1
- IndexError in DataLoader Worker Process with Custom Dataset
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