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Merged
BTheDragonMaster merged 2 commits into from
Oct 7, 2025
Merged

Merge dev into main #2

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ad2f6c7
Code cleanup
BTheDragonMaster Oct 7, 2025
2cd77b5
Add 'full model finetuning' config type
BTheDragonMaster Oct 7, 2025
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2 changes: 1 addition & 1 deletion mewtwo/machine_learning/data_preparation/test/test_calculate_sample_weights.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@

from mewtwo.machine_learning.data_preparation.calculate_sample_weights import get_sample_weights


class CalculateSampleWeights(unittest.TestCase):
def test_get_sample_weights(self):
dataset_1 = [0.1, 0.3, 0.5, 0.7, 0.9]
Expand All @@ -22,6 +23,5 @@ def assertNearlyEqual(self, list_1, list_2):
self.fail(f"Lists are not equal: {list_1}, {list_2}. \n First mismatching element: {i} ([{element_1}], [{element_2}])")



if __name__ == "__main__":
unittest.main()
1 change: 1 addition & 0 deletions mewtwo/machine_learning/transformer/config/config_types.py
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Expand Up @@ -33,6 +33,7 @@ def from_string_description(string_description) -> "LossFunctionType":
class FinetuningType(Enum):
LINEAR_HEAD = 1
ADAPTER = 2
FULL = 3

@staticmethod
def from_string_description(string_description) -> "FinetuningType":
Expand Down
9 changes: 5 additions & 4 deletions mewtwo/machine_learning/transformer/finetune_bert.py
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@@ -1,7 +1,8 @@
import argparse
import os
from typing import TextIO

from mewtwo.machine_learning.transformer.model import load_model
from mewtwo.machine_learning.transformer.model import load_model, Model
from mewtwo.machine_learning.transformer.config.config_types import SchedulerType, EarlyStoppingMetricType

from scipy.stats import pearsonr, spearmanr
Expand Down Expand Up @@ -34,7 +35,7 @@ def parse_arguments() -> argparse.Namespace:
return args


def metric_has_improved(old_metric, new_metric, metric_type):
def metric_has_improved(old_metric: float, new_metric: float, metric_type: EarlyStoppingMetricType) -> bool:
if metric_type in EarlyStoppingMetricType.MAX_METRICS:
if new_metric > old_metric:
return True
Expand All @@ -49,7 +50,7 @@ def metric_has_improved(old_metric, new_metric, metric_type):
raise ValueError(f"Unrecognised early stopping metric: {metric_type.name}")


def get_metric(eval_loss, pearson, spearman, metric_type):
def get_metric(eval_loss: float, pearson: float, spearman: float, metric_type: EarlyStoppingMetricType) -> float:
if metric_type == EarlyStoppingMetricType.PEARSON_R:
return pearson
elif metric_type == EarlyStoppingMetricType.SPEARMAN_R:
Expand All @@ -60,7 +61,7 @@ def get_metric(eval_loss, pearson, spearman, metric_type):
raise ValueError(f"Unrecognised early stopping metric: {metric_type.name}")


def finetune(model, summary, epochs, out_dir, header=False):
def finetune(model: Model, summary: TextIO, epochs: int, out_dir: str, header=False) -> None:
if header:
summary.write("epoch\taverage_train_loss\taverage_eval_loss\tpearsonr\tspearmanr\n")
config_file = os.path.join(out_dir, "model.config")
Expand Down
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