query_id
stringlengths
4
5
corpus_id
stringlengths
4
4
score
int64
1
1
q566
c371
1
q568
c372
1
q569
c373
1
q570
c374
1
q571
c375
1
q572
c376
1
q573
c377
1
q576
c378
1
q577
c379
1
q578
c380
1
q579
c381
1
q580
c382
1
q581
c383
1
q582
c384
1
q583
c385
1
q584
c386
1
q585
c387
1
q586
c388
1
q587
c389
1
q588
c390
1
q591
c391
1
q592
c392
1
q593
c393
1
q594
c394
1
q595
c395
1
q596
c396
1
q597
c397
1
q598
c398
1
q600
c399
1
q602
c400
1
q603
c401
1
q604
c402
1
q605
c403
1
q606
c404
1
q607
c405
1
q608
c406
1
q610
c407
1
q611
c408
1
q613
c409
1
q614
c410
1
q615
c411
1
q616
c412
1
q617
c413
1
q618
c414
1
q619
c415
1
q620
c416
1
q621
c417
1
q622
c418
1
q623
c419
1
q624
c420
1
q625
c421
1
q626
c422
1
q627
c423
1
q628
c424
1
q629
c425
1
q630
c426
1
q631
c427
1
q632
c428
1
q633
c429
1
q634
c430
1
q636
c431
1
q637
c432
1
q638
c433
1
q639
c434
1
q641
c435
1
q642
c436
1
q643
c437
1
q644
c438
1
q645
c439
1
q646
c440
1
q647
c441
1
q648
c442
1
q649
c443
1
q650
c444
1
q651
c445
1
q652
c446
1
q653
c447
1
q654
c448
1
q655
c449
1
q656
c450
1
q658
c451
1
q659
c452
1
q660
c453
1
q661
c454
1
q662
c455
1
q663
c456
1
q664
c457
1
q665
c458
1
q666
c459
1
q667
c460
1
q669
c461
1
q670
c462
1
q671
c463
1
q672
c464
1
q673
c465
1
q674
c466
1
q675
c467
1
q680
c468
1
q681
c469
1
q682
c470
1

Employing the COIR evaluation framework's dataset version, utilize the code below for assessment:

import coir
from coir.data_loader import get_tasks
from coir.evaluation import COIR
from coir.models import YourCustomDEModel

model_name = "intfloat/e5-base-v2"

# Load the model
model = YourCustomDEModel(model_name=model_name)

# Get tasks
#all task ["codetrans-dl","stackoverflow-qa","apps","codefeedback-mt","codefeedback-st","codetrans-contest","synthetic-
# text2sql","cosqa","codesearchnet","codesearchnet-ccr"]
tasks = get_tasks(tasks=["codetrans-contest"])

# Initialize evaluation
evaluation = COIR(tasks=tasks,batch_size=128)

# Run evaluation
results = evaluation.run(model, output_folder=f"results/{model_name}")
print(results)
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