Comments (3)
kpe
commented on August 14, 2024
1
@muhammadfahid51 - Currently bert-for-tf2 does not have an example or tools for pre-training from scratch. When pre-training from scratch it might be easier using the workflow from the original google-research/bert. Once you have the pre-trained weights, you could fine-tune with bert-for-tf2.
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muhammadfahid51
commented on August 14, 2024
Yeah I got it. Will you add it ?
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kpe
commented on August 14, 2024
yes, I'll be adding support for pre-training from scratch or continuing pre-training as part of #13 (but it might take some time).
Closing for now, and handling this in #13.
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Related Issues (20)
- ResourceExhaustedError: OOM when allocating tensor with shape[501153,768] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:Mul]
- mixed precision HOT 3
- example (gpu_movie_reviews) has some mistake
- Failed to get weights from pretrained google model HOT 2
- Can not load pretrained bert weights when loading chinese_L-12_H-768_A-12/bert_model.ckpt HOT 3
- Paddings must be non-negative
- albert classification error(Failed copying input tensor from GPU in order to run Identity: GPU sync failed [Op:Identity])
- ValueError: Found unexpected keys that do not correspond to any Model output
- More comments for the code
- Can't train BERT with loaded weights on QA Task HOT 3
- Setting unexpected parameter 'name' in Params instance 'Params' HOT 2
- how to using this in functional model
- may be there is some problem work with tf hub
- AttributeError: module 'bert' has no attribute 'Layer'
- type error HOT 5
- Activation after bert-layer differs
- Count of weight not found[196]
- OSS License compatibility question
- tensorflow.python.keras.layer.input_spec should be replaced with tensorflow.keras.layers.InputSpec HOT 1
- setuptools.convert_path removed
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