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# lightning.pytorch==2.4.0
seed_everything: 42
trainer:
accelerator: auto
strategy:
class_path: lightning.pytorch.strategies.DDPStrategy
init_args:
accelerator: null
parallel_devices: null
cluster_environment: null
checkpoint_io: null
precision_plugin: null
ddp_comm_state: null
ddp_comm_hook: null
ddp_comm_wrapper: null
model_averaging_period: null
process_group_backend: null
timeout: 0:30:00
start_method: popen
output_device: null
dim: 0
broadcast_buffers: true
process_group: null
bucket_cap_mb: 25
find_unused_parameters: false
check_reduction: false
gradient_as_bucket_view: false
static_graph: false
delay_all_reduce_named_params: null
param_to_hook_all_reduce: null
mixed_precision: null
device_mesh: null
devices: auto
num_nodes: 8
precision: 32
logger:
class_path: lightning.pytorch.loggers.WandbLogger
init_args:
name: 7B_splice_reconstruction
save_dir: logs
version: null
offline: false
dir: null
id: null
anonymous: null
project: MGEN_AIDO.DNA-7B_GUE
log_model: false
experiment: null
prefix: ''
checkpoint_name: null
job_type: null
config: null
entity: null
reinit: null
tags: null
group: null
notes: null
magic: null
config_exclude_keys: null
config_include_keys: null
mode: null
allow_val_change: null
resume: null
force: null
tensorboard: null
sync_tensorboard: null
monitor_gym: null
save_code: true
settings: null
callbacks:
- class_path: lightning.pytorch.callbacks.LearningRateMonitor
init_args:
logging_interval: step
log_momentum: false
log_weight_decay: false
- class_path: lightning.pytorch.callbacks.ModelCheckpoint # save ckpt at the end of each epoch, and save the best val_mcc ckpt
init_args:
dirpath: null
filename: epoch_{epoch}-val_mcc:{val_mcc:.3f}
monitor: val_mcc
verbose: false
save_last: true
save_top_k: 1
save_weights_only: false
mode: max
auto_insert_metric_name: true
every_n_train_steps: null
train_time_interval: null
every_n_epochs: 1
save_on_train_epoch_end: null
enable_version_counter: true
- class_path: lightning.pytorch.callbacks.early_stopping.EarlyStopping
dict_kwargs:
monitor: val_mcc
mode: max
patience: 10
fast_dev_run: false
max_epochs: 20
min_epochs: null
max_steps: -1
min_steps: null
max_time: null
limit_train_batches: null
limit_val_batches: null
limit_test_batches: null
limit_predict_batches: null
overfit_batches: 0.0
val_check_interval: null
check_val_every_n_epoch: 1
num_sanity_val_steps: null
log_every_n_steps: 50
enable_checkpointing: null
enable_progress_bar: null
enable_model_summary: null
accumulate_grad_batches: 1
gradient_clip_val: 1
gradient_clip_algorithm: null
deterministic: null
benchmark: null
inference_mode: true
use_distributed_sampler: true
profiler:
class_path: lightning.pytorch.profilers.PyTorchProfiler
init_args:
dirpath: null
filename: null
group_by_input_shapes: false
emit_nvtx: false
export_to_chrome: true
row_limit: 20
sort_by_key: null
record_module_names: true
table_kwargs: null
record_shapes: false
dict_kwargs:
profile_memory: true
detect_anomaly: false
barebones: false
plugins: null
sync_batchnorm: false
reload_dataloaders_every_n_epochs: 0
default_root_dir: logs
model:
class_path: modelgenerator.tasks.SequenceClassification
init_args:
backbone:
class_path: modelgenerator.backbones.aido_dna_7b
init_args:
from_scratch: false
use_peft: true
save_peft_only: true
lora_r: 16
lora_alpha: 32
lora_dropout: 0.1
config_overwrites: null
model_init_args: null
max_length: 402
adapter:
class_path: modelgenerator.adapters.MLPPoolAdapter
init_args:
pooling: mean_pooling
hidden_sizes:
- 128
bias: true
dropout: 0.1
dropout_in_middle: false
n_classes: 3
optimizer:
class_path: torch.optim.AdamW
init_args:
lr: 0.0005
betas:
- 0.9
- 0.95
eps: 1.0e-08
weight_decay: 0.1
amsgrad: false
maximize: false
foreach: null
capturable: false
differentiable: false
fused: null
lr_scheduler:
class_path: modelgenerator.lr_schedulers.CosineWithWarmup
init_args:
warmup_ratio: 0.1
use_legacy_adapter: false
strict_loading: true
reset_optimizer_states: false
data:
class_path: modelgenerator.data.GUEClassification
init_args:
hf_name: leannmlindsey/GUE
task: splice_reconstructed
x_col: sequence
y_col: label
train_split_name: train
test_split_name: test
valid_split_name: null
valid_split_size: 0.1
batch_size: 4
shuffle: true
sampler: null
num_workers: 0
pin_memory: true
persistent_workers: false
ckpt_path: null
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