From 53c702724e176a8ecbe0361bc3112c8f2a504601 Mon Sep 17 00:00:00 2001
From: servan <christophe.servan@lisn.upsaclay.fr>
Date: Mon, 12 Jun 2023 13:38:03 +0200
Subject: [PATCH] updated to change output directories
---
_tagging-hf-MEDIA-COST.py | 20 ++++++++++----------
1 file changed, 10 insertions(+), 10 deletions(-)
diff --git a/_tagging-hf-MEDIA-COST.py b/_tagging-hf-MEDIA-COST.py
index 065abf1..eb8063b 100644
--- a/_tagging-hf-MEDIA-COST.py
+++ b/_tagging-hf-MEDIA-COST.py
@@ -147,7 +147,7 @@ tokenized_datasets = datasets.map(tokenize_and_align_labels, batched=True)
model = AutoModelForTokenClassification.from_pretrained(model_checkpoint, num_labels=len(label_list))
args = TrainingArguments(
- f"models/media/"+model_checkpoint.replace("/","_"),
+ f"models/media/"+"outputs_" + model_checkpoint.replace("/","_"),
evaluation_strategy = "epoch",
learning_rate=2e-5,
per_device_train_batch_size=batch_size,
@@ -166,8 +166,8 @@ metric = load_metric("seqeval")
#example["tokens"]
-labels = [label_list[i] for i in example[f"{task}_tags"]]
-metric.compute(predictions=[labels], references=[labels])
+#labels = [label_list[i] for i in example[f"{task}_tags"]]
+#metric.compute(predictions=[labels], references=[labels])
@@ -216,10 +216,10 @@ trainer = Trainer(
)
-if not os.path.exists(model_checkpoint.replace("/","_") + "/ImpactTrackerTrain"):
- os.makedirs(model_checkpoint.replace("/","_") + "/ImpactTrackerTrain")
-if not os.path.exists(model_checkpoint.replace("/","_") + "/ImpactTrackerTest"):
- os.makedirs(model_checkpoint.replace("/","_") + "/ImpactTrackerTest")
+if not os.path.exists("outputs_" + model_checkpoint.replace("/","_") + "/ImpactTrackerTrain"):
+ os.makedirs("outputs_" + model_checkpoint.replace("/","_") + "/ImpactTrackerTrain")
+if not os.path.exists("outputs_" + model_checkpoint.replace("/","_") + "/ImpactTrackerTest"):
+ os.makedirs("outputs_" + model_checkpoint.replace("/","_") + "/ImpactTrackerTest")
tracker = OfflineEmissionsTracker(country_iso_code="FRA")
#tracker_plop = ImpactTracker('.')
#tracker_plop.launch_impact_monitor()
@@ -232,7 +232,7 @@ to_train = True
to_evaluate = True
if to_train:
- impact_dir = model_checkpoint.replace("/","_") + "/ImpactTrackerTrain"
+ impact_dir = "outputs_" + model_checkpoint.replace("/","_") + "/ImpactTrackerTrain"
myimpacttrackertrain = ImpactTracker(impact_dir)
myimpacttrackertrain.launch_impact_monitor()
trainer.train()
@@ -245,7 +245,7 @@ tracker_test = OfflineEmissionsTracker(country_iso_code="FRA")
tracker_test.start()
if to_evaluate:
- impact_dir = model_checkpoint.replace("/","_") + "/ImpactTrackerTest"
+ impact_dir = "outputs_" + model_checkpoint.replace("/","_") + "/ImpactTrackerTest"
myimpacttrackerinference = ImpactTracker(impact_dir)
myimpacttrackerinference.launch_impact_monitor()
trainer.evaluate(eval_dataset=tokenized_datasets["test"])
@@ -268,6 +268,6 @@ emissions: float = tracker_test.stop()
#print(classification_report(true_predictions, true_labels))
print(print_results(results))
-shutil.move("emissions.csv",model_checkpoint.replace("/","_") + "/emissions.csv")
+shutil.move("emissions.csv","outputs_" + model_checkpoint.replace("/","_") + "/emissions.csv")
--
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