Esm2 on Sagemaker Hyperpod #387
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Signed-off-by: Ankur Srivastava <[email protected]>
Signed-off-by: Ankur Srivastava <[email protected]>
Signed-off-by: Ankur Srivastava <[email protected]>
Signed-off-by: Ankur Srivastava <[email protected]>
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Do we have any SMHP specific feature in this test case? see also #381 |
KeitaW
reviewed
Jul 30, 2024
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| | Model | device_batch_size | num_nodes | torch.compile | Instance | Throughput | | ||
| |:------:|:-----------------:|:---------:|:-------------:| :------------: | :------------: | | ||
| | ESM2 | 8 | 2 | No | g5.12xlarge | 160 samples/s | |
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The set up instruction advise to use 24xl but actually 12xl was used?
KeitaW
reviewed
Jul 30, 2024
| ## What is ESM-2? | ||
| [ESM-2](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v1) is a pLM trained using unsupervied masked language modelling on 250 Million protein sequences by researchers at [Facebook AI Research (FAIR)](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v1). It is available in several sizes, ranging from 8 Million to 15 Billion parameters. The smaller models are suitable for various sequence and token classification tasks. The FAIR team also adapted the 3 Billion parameter version into the ESMFold protein structure prediction algorithm. They have since used ESMFold to predict the struture of [more than 700 Million metagenomic proteins](https://esmatlas.com/about). | ||
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| ESM-2 is a powerful pLM. We will demonstrate how to use QLoRA to fine-tune ESM-2 on g5.24xlarge instances. We will use ESM-2 to predict [subcellular localization](https://academic.oup.com/nar/article/50/W1/W228/6576357?login=false). Understanding where proteins appear in cells can help us understand their role in disease and find new drug targets. |
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Is this test case demonstrating pretraining? or finetuning? I believe latter but the title states former.
KeitaW
reviewed
Jul 30, 2024
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| # How to pretrain ESM2 with SageMaker Hyperpod using Amazon G5 instances | |||
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Suggested change
| # How to pretrain ESM2 with SageMaker Hyperpod using Amazon G5 instances | |
| # How to finetune ESM2 with SageMaker Hyperpod using Amazon G5 instances |
KeitaW
reviewed
Jul 30, 2024
| #!/bin/bash | ||
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| #SBATCH --job-name=esm2-accelerate | ||
| #SBATCH -D . |
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Suggested change
| #SBATCH -D . |
This line may not be necessary.
-D, --chdir=
Set the working directory of the batch script to directory before it is executed. The path can be specified as full path or relative path to the directory where the command is executed.
KeitaW
reviewed
Jul 30, 2024
| # SPDX-License-Identifier: MIT-0 | ||
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| #SBATCH --nodes=2 # number of nodes to use | ||
| #SBATCH --job-name=FSDP # name of your job |
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Suggested change
| #SBATCH --job-name=FSDP # name of your job | |
| #SBATCH --job-name=DDP # name of your job |
KeitaW
reviewed
Jul 30, 2024
| #SBATCH -D . | ||
| #SBATCH --output=accelerate-%x.%j.out | ||
| #SBATCH --nodes=2 # number of nodes | ||
| #SBATCH --ntasks-per-node=1 # number of MP tasks |
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Suggested change
| #SBATCH --ntasks-per-node=1 # number of MP tasks | |
| #SBATCH --exclusive # job has exclusive use of the resource, no sharing |
instead?
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