AutoTrain Python automatically using MPS on Mac - How to switch to CPU

Lyreck
Fri, 08 Nov 2024 23:20:16 +0000

Hello everyone,

I am trying to fine-tune cardiffnlp/twitter-xlm-roberta-base-sentiment with some additional text. I am using the Python API to setup the model.

Everything appears to work just fine, the only thing is that I encounter a memory shortage with MPS (I am working on a 2019 MacBook Pro with AMD Radeon):

MPS backend out of memory (MPS allocated: 5.69 GB, other allocations: 1.00 GB, max allowed: 6.77 GB). Tried to allocate 96.00 MB on private pool. Use PYTORCH_MPS_HIGH_WATERMARK_RATIO=0.0 to disable upper limit for memory allocations (may cause system failure).

From what I understand, this is a physical limitation from my computer (perhaps I’m wrong - it’s surprising since the model is supposedly less than 2GB large)). Would it be possible to switch to CPU training rather than GPU training ? I don’t see any parameter in the model that seems to control that.

Any help or idea is welcome !

Here is the code I am using:

from autotrain.params import TextClassificationParams
from autotrain.project import AutoTrainProject

HF_USERNAME = ""
HF_TOKEN = ""

params = TextClassificationParams(
    model="cardiffnlp/twitter-xlm-roberta-base-sentiment",
    data_path="data/", #"Lyreck/tiktok_brat_comments", # path to the dataset on huggingface hub
    text_column="text", # the column in the dataset that contains the text
    target_column="label", # the column in the dataset that contains the labels
    train_split="train",
    valid_split="validation",
    epochs=3,
    batch_size=8,
    max_seq_length=512,
    lr=1e-5,
    optimizer="adamw_torch",
    scheduler="linear",
    gradient_accumulation=1,
    #mixed_precision="fp16", #need graphic card for this (no mps available)
    project_name="finetuned-sentiment-model",
    log="tensorboard",
    push_to_hub=True,
    username=HF_USERNAME,
    token=HF_TOKEN,
)

project = AutoTrainProject(params=params, backend="local", process=True)
project.create()```

Thanks!

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