bytedance / bytedance/1d-tokenizer
Training on new dataset
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Description
Hi I am looking to train this tokenizer on a sign language dataset CSL-Daily so that I can compress video frames into 32 tokens.
However, I am not getting very good results (attached below). I would like to check if all I have to do is download the pretrained model and then run it as:
WANDB_MODE=offline accelerate launch --num_machines=1 --num_processes=2 --machine_rank=0 --main_process_ip=127.0.0.1 --main_process_port=9999 --same_network scripts/train_titok.py config=configs/training/stage1/titok_;32.yaml \
experiment.project="titok_l32_stage1" \
experiment.name="titok_;32_stage1_run1" \
experiment.output_dir="titok_l32_stage1_run1" \
training.per_gpu_batch_size=32
Please advice! Thanks!
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Research direction
Start by reviewing scripts/train_titok.py and configs/training/stage1/titok_;32.yaml, then compare the reported CSL-Daily results with the training command in the issue. Done means determining whether this pretrained-model workflow is sufficient for the requested 32-token sign-language dataset training and documenting the required setup or changes.
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Assessment
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100