forked from pytorch/torchtune
-
Notifications
You must be signed in to change notification settings - Fork 0
/
mini_full_low_memory.yaml
77 lines (69 loc) · 2.2 KB
/
mini_full_low_memory.yaml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
# Config for single device full finetuning in full_finetune_single_device.py
# using a Phi3 Mini 4K Instruct
#
# This config assumes that you've run the following command before launching
# this run:
# tune download microsoft/Phi-3-mini-4k-instruct --output-dir /tmp/Phi-3-mini-4k-instruct --ignore-patterns None --hf-token <HF_TOKEN>
#
# The default config uses an optimizer from bitsandbytes. If you do not have it installed,
# you can install it with
# pip install bitsandbytes
#
# To launch on a single device, run the following command from root:
# tune run full_finetune_single_device --config phi3/mini_full_low_memory
#
# You can add specific overrides through the command line. For example
# to override the checkpointer directory while launching training
# you can run:
# tune run full_finetune_single_device --config phi3/mini_full_low_memory checkpointer.checkpoint_dir=<YOUR_CHECKPOINT_DIR>
#
# This config works only for training on single device.
# Model arguments
model:
_component_: torchtune.models.phi3.phi3_mini
# Tokenizer
tokenizer:
_component_: torchtune.models.phi3.phi3_mini_tokenizer
path: /tmp/Phi-3-mini-4k-instruct/tokenizer.model
max_seq_len: null
# Checkpointer
checkpointer:
_component_: torchtune.training.FullModelHFCheckpointer
checkpoint_dir: /tmp/Phi-3-mini-4k-instruct
checkpoint_files: [
model-00001-of-00002.safetensors,
model-00002-of-00002.safetensors
]
recipe_checkpoint: null
output_dir: /tmp/Phi-3-mini-4k-instruct
model_type: PHI3_MINI
resume_from_checkpoint: False
# Dataset
dataset:
_component_: torchtune.datasets.alpaca_cleaned_dataset
seed: null
shuffle: True
# Fine-tuning arguments
epochs: 1
max_steps_per_epoch: null
batch_size: 2
gradient_accumulation_steps: 1
optimizer:
_component_: bitsandbytes.optim.PagedAdamW
lr: 5e-6
optimizer_in_bwd: True
loss:
_component_: torchtune.modules.loss.CEWithChunkedOutputLoss
compile: False
# Training env
device: cuda
# Memory management
enable_activation_checkpointing: True
dtype: bf16
# Logging
output_dir: /tmp/phi3_finetune_output
metric_logger:
_component_: torchtune.training.metric_logging.DiskLogger
log_dir: /tmp/Phi-3-mini-4k-instruct/logs
log_every_n_steps: 1
log_peak_memory_stats: False