System Info

• transformers version: 4.43.0.dev0
• Platform: macOS-14.4.1-arm64-arm-64bit
• Python version: 3.9.13
• Huggingface_hub version: 0.23.4
• Safetensors version: 0.4.3
• Accelerate version: 0.31.0
• Accelerate config: - compute_environment: LOCAL_MACHINE
  - distributed_type: NO
  - mixed_precision: no
  - use_cpu: False
  - debug: False
  - num_processes: 1
  - machine_rank: 0
  - num_machines: 1
  - rdzv_backend: static
  - same_network: True
  - main_training_function: main
  - enable_cpu_affinity: False
  - downcast_bf16: no
  - tpu_use_cluster: False
  - tpu_use_sudo: False
  - tpu_env: []
• PyTorch version (GPU?): 2.3.1 (False)
• Tensorflow version (GPU?): not installed (NA)
• Flax version (CPU?/GPU?/TPU?): not installed (NA)
• Jax version: not installed
• JaxLib version: not installed
• Using distributed or parallel set-up in script?:

Who can help?

@muellerzr @SunMarc

Information

• The official example scripts
• My own modified scripts

Tasks

• An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
• My own task or dataset (give details below)

Reproduction

Execute the following code using accelerate with MPS accelerator.

from transformers import TrainingArguments

training_args = TrainingArguments(output_dir = "tmp_trainer")
print(training_args.device)

Expected behavior

I expect to see mps will be displayed. However, I see cpu.