SetFit with BAAI/bge-large-en-v1.5
This is a SetFit model that can be used for Text Classification. This SetFit model uses BAAI/bge-large-en-v1.5 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.
The model has been trained using an efficient few-shot learning technique that involves:
- Fine-tuning a Sentence Transformer with contrastive learning.
- Training a classification head with features from the fine-tuned Sentence Transformer.
Model Details
Model Description
- Model Type: SetFit
- Sentence Transformer body: BAAI/bge-large-en-v1.5
- Classification head: a LogisticRegression instance
- Maximum Sequence Length: 512 tokens
- Number of Classes: 7 classes
Model Sources
- Repository: SetFit on GitHub
- Paper: Efficient Few-Shot Learning Without Prompts
- Blogpost: SetFit: Efficient Few-Shot Learning Without Prompts
Model Labels
Label | Examples |
---|---|
Generalreply |
|
Lookup_1 |
|
Tablejoin |
|
Rejection |
|
Aggregation |
|
Viewtables |
|
Lookup |
|
Evaluation
Metrics
Label | Accuracy |
---|---|
all | 0.5726 |
Uses
Direct Use for Inference
First install the SetFit library:
pip install setfit
Then you can load this model and run inference.
from setfit import SetFitModel
# Download from the 🤗 Hub
model = SetFitModel.from_pretrained("nazhan/bge-large-en-v1.5-brahmaputra-iter-9-1-epoch")
# Run inference
preds = model("Get me avg Intangible Assets.")
Training Details
Training Set Metrics
Training set | Min | Median | Max |
---|---|---|---|
Word count | 2 | 8.7792 | 62 |
Label | Training Sample Count |
---|---|
Tablejoin | 126 |
Rejection | 72 |
Aggregation | 221 |
Lookup | 62 |
Generalreply | 60 |
Viewtables | 73 |
Lookup_1 | 224 |
Training Hyperparameters
- batch_size: (16, 16)
- num_epochs: (1, 1)
- max_steps: -1
- sampling_strategy: oversampling
- body_learning_rate: (2e-05, 1e-05)
- head_learning_rate: 0.01
- loss: CosineSimilarityLoss
- distance_metric: cosine_distance
- margin: 0.25
- end_to_end: False
- use_amp: False
- warmup_proportion: 0.1
- seed: 42
- eval_max_steps: -1
- load_best_model_at_end: True
Training Results
Epoch | Step | Training Loss | Validation Loss |
---|---|---|---|
0.0000 | 1 | 0.2059 | - |
0.0014 | 50 | 0.1956 | - |
0.0028 | 100 | 0.207 | - |
0.0042 | 150 | 0.1783 | - |
0.0056 | 200 | 0.1517 | - |
0.0070 | 250 | 0.1795 | - |
0.0084 | 300 | 0.1227 | - |
0.0098 | 350 | 0.063 | - |
0.0112 | 400 | 0.0451 | - |
0.0126 | 450 | 0.0408 | - |
0.0140 | 500 | 0.0576 | - |
0.0155 | 550 | 0.0178 | - |
0.0169 | 600 | 0.0244 | - |
0.0183 | 650 | 0.0072 | - |
0.0197 | 700 | 0.0223 | - |
0.0211 | 750 | 0.0046 | - |
0.0225 | 800 | 0.003 | - |
0.0239 | 850 | 0.004 | - |
0.0253 | 900 | 0.0042 | - |
0.0267 | 950 | 0.0047 | - |
0.0281 | 1000 | 0.0045 | - |
0.0295 | 1050 | 0.0032 | - |
0.0309 | 1100 | 0.0021 | - |
0.0323 | 1150 | 0.0028 | - |
0.0337 | 1200 | 0.0022 | - |
0.0351 | 1250 | 0.0024 | - |
0.0365 | 1300 | 0.0019 | - |
0.0379 | 1350 | 0.002 | - |
0.0393 | 1400 | 0.0015 | - |
0.0407 | 1450 | 0.0016 | - |
0.0421 | 1500 | 0.0014 | - |
0.0436 | 1550 | 0.0013 | - |
0.0450 | 1600 | 0.0016 | - |
0.0464 | 1650 | 0.0011 | - |
0.0478 | 1700 | 0.0012 | - |
0.0492 | 1750 | 0.0011 | - |
0.0506 | 1800 | 0.0015 | - |
0.0520 | 1850 | 0.0016 | - |
0.0534 | 1900 | 0.0012 | - |
0.0548 | 1950 | 0.0008 | - |
0.0562 | 2000 | 0.0011 | - |
0.0576 | 2050 | 0.001 | - |
0.0590 | 2100 | 0.001 | - |
0.0604 | 2150 | 0.0008 | - |
0.0618 | 2200 | 0.0009 | - |
0.0632 | 2250 | 0.0007 | - |
0.0646 | 2300 | 0.0008 | - |
0.0660 | 2350 | 0.0006 | - |
0.0674 | 2400 | 0.0007 | - |
0.0688 | 2450 | 0.0008 | - |
0.0702 | 2500 | 0.0006 | - |
0.0717 | 2550 | 0.0007 | - |
0.0731 | 2600 | 0.0006 | - |
0.0745 | 2650 | 0.0007 | - |
0.0759 | 2700 | 0.0005 | - |
0.0773 | 2750 | 0.0006 | - |
0.0787 | 2800 | 0.0007 | - |
0.0801 | 2850 | 0.0007 | - |
0.0815 | 2900 | 0.0005 | - |
0.0829 | 2950 | 0.0008 | - |
0.0843 | 3000 | 0.0005 | - |
0.0857 | 3050 | 0.0007 | - |
0.0871 | 3100 | 0.0006 | - |
0.0885 | 3150 | 0.0005 | - |
0.0899 | 3200 | 0.0007 | - |
0.0913 | 3250 | 0.0005 | - |
0.0927 | 3300 | 0.0004 | - |
0.0941 | 3350 | 0.0005 | - |
0.0955 | 3400 | 0.0003 | - |
0.0969 | 3450 | 0.0004 | - |
0.0983 | 3500 | 0.0004 | - |
0.0998 | 3550 | 0.0004 | - |
0.1012 | 3600 | 0.0004 | - |
0.1026 | 3650 | 0.0004 | - |
0.1040 | 3700 | 0.0004 | - |
0.1054 | 3750 | 0.0004 | - |
0.1068 | 3800 | 0.0003 | - |
0.1082 | 3850 | 0.0003 | - |
0.1096 | 3900 | 0.0005 | - |
0.1110 | 3950 | 0.0005 | - |
0.1124 | 4000 | 0.0005 | - |
0.1138 | 4050 | 0.0003 | - |
0.1152 | 4100 | 0.0006 | - |
0.1166 | 4150 | 0.0004 | - |
0.1180 | 4200 | 0.0003 | - |
0.1194 | 4250 | 0.0004 | - |
0.1208 | 4300 | 0.0003 | - |
0.1222 | 4350 | 0.0004 | - |
0.1236 | 4400 | 0.0003 | - |
0.1250 | 4450 | 0.0003 | - |
0.1264 | 4500 | 0.0004 | - |
0.1279 | 4550 | 0.0003 | - |
0.1293 | 4600 | 0.0005 | - |
0.1307 | 4650 | 0.0004 | - |
0.1321 | 4700 | 0.0003 | - |
0.1335 | 4750 | 0.0004 | - |
0.1349 | 4800 | 0.0003 | - |
0.1363 | 4850 | 0.0003 | - |
0.1377 | 4900 | 0.0003 | - |
0.1391 | 4950 | 0.0003 | - |
0.1405 | 5000 | 0.0003 | - |
0.1419 | 5050 | 0.0003 | - |
0.1433 | 5100 | 0.0004 | - |
0.1447 | 5150 | 0.0003 | - |
0.1461 | 5200 | 0.0004 | - |
0.1475 | 5250 | 0.0004 | - |
0.1489 | 5300 | 0.0003 | - |
0.1503 | 5350 | 0.0003 | - |
0.1517 | 5400 | 0.0003 | - |
0.1531 | 5450 | 0.0003 | - |
0.1545 | 5500 | 0.0002 | - |
0.1560 | 5550 | 0.0003 | - |
0.1574 | 5600 | 0.0003 | - |
0.1588 | 5650 | 0.0003 | - |
0.1602 | 5700 | 0.0002 | - |
0.1616 | 5750 | 0.0002 | - |
0.1630 | 5800 | 0.0003 | - |
0.1644 | 5850 | 0.0002 | - |
0.1658 | 5900 | 0.0003 | - |
0.1672 | 5950 | 0.0002 | - |
0.1686 | 6000 | 0.0002 | - |
0.1700 | 6050 | 0.0002 | - |
0.1714 | 6100 | 0.0002 | - |
0.1728 | 6150 | 0.0003 | - |
0.1742 | 6200 | 0.0003 | - |
0.1756 | 6250 | 0.0003 | - |
0.1770 | 6300 | 0.0003 | - |
0.1784 | 6350 | 0.0002 | - |
0.1798 | 6400 | 0.0003 | - |
0.1812 | 6450 | 0.0002 | - |
0.1826 | 6500 | 0.0003 | - |
0.1841 | 6550 | 0.0002 | - |
0.1855 | 6600 | 0.0002 | - |
0.1869 | 6650 | 0.0002 | - |
0.1883 | 6700 | 0.0002 | - |
0.1897 | 6750 | 0.0003 | - |
0.1911 | 6800 | 0.0003 | - |
0.1925 | 6850 | 0.0002 | - |
0.1939 | 6900 | 0.0002 | - |
0.1953 | 6950 | 0.0002 | - |
0.1967 | 7000 | 0.0002 | - |
0.1981 | 7050 | 0.0001 | - |
0.1995 | 7100 | 0.0002 | - |
0.2009 | 7150 | 0.0002 | - |
0.2023 | 7200 | 0.0002 | - |
0.2037 | 7250 | 0.0002 | - |
0.2051 | 7300 | 0.0002 | - |
0.2065 | 7350 | 0.0001 | - |
0.2079 | 7400 | 0.0002 | - |
0.2093 | 7450 | 0.0024 | - |
0.2107 | 7500 | 0.0718 | - |
0.2122 | 7550 | 0.1 | - |
0.2136 | 7600 | 0.1876 | - |
0.2150 | 7650 | 0.1006 | - |
0.2164 | 7700 | 0.163 | - |
0.2178 | 7750 | 0.1008 | - |
0.2192 | 7800 | 0.1073 | - |
0.2206 | 7850 | 0.2059 | - |
0.2220 | 7900 | 0.112 | - |
0.2234 | 7950 | 0.1103 | - |
0.2248 | 8000 | 0.1921 | - |
0.2262 | 8050 | 0.0641 | - |
0.2276 | 8100 | 0.0992 | - |
0.2290 | 8150 | 0.2486 | - |
0.2304 | 8200 | 0.1716 | - |
0.2318 | 8250 | 0.142 | - |
0.2332 | 8300 | 0.1431 | - |
0.2346 | 8350 | 0.1774 | - |
0.2360 | 8400 | 0.1537 | - |
0.2374 | 8450 | 0.1902 | - |
0.2388 | 8500 | 0.1015 | - |
0.2402 | 8550 | 0.1401 | - |
0.2417 | 8600 | 0.2599 | - |
0.2431 | 8650 | 0.261 | - |
0.2445 | 8700 | 0.1861 | - |
0.2459 | 8750 | 0.1743 | - |
0.2473 | 8800 | 0.1705 | - |
0.2487 | 8850 | 0.1752 | - |
0.2501 | 8900 | 0.0914 | - |
0.2515 | 8950 | 0.1651 | - |
0.2529 | 9000 | 0.1165 | - |
0.2543 | 9050 | 0.2675 | - |
0.2557 | 9100 | 0.0953 | - |
0.2571 | 9150 | 0.0713 | - |
0.2585 | 9200 | 0.1782 | - |
0.2599 | 9250 | 0.1995 | - |
0.2613 | 9300 | 0.2393 | - |
0.2627 | 9350 | 0.1734 | - |
0.2641 | 9400 | 0.2222 | - |
0.2655 | 9450 | 0.3005 | - |
0.2669 | 9500 | 0.2252 | - |
0.2683 | 9550 | 0.2498 | - |
0.2698 | 9600 | 0.3293 | - |
0.2712 | 9650 | 0.2422 | - |
0.2726 | 9700 | 0.1943 | - |
0.2740 | 9750 | 0.2497 | - |
0.2754 | 9800 | 0.2538 | - |
0.2768 | 9850 | 0.2114 | - |
0.2782 | 9900 | 0.1719 | - |
0.2796 | 9950 | 0.2453 | - |
0.2810 | 10000 | 0.2571 | - |
0.2824 | 10050 | 0.2267 | - |
0.2838 | 10100 | 0.2274 | - |
0.2852 | 10150 | 0.2441 | - |
0.2866 | 10200 | 0.2536 | - |
0.2880 | 10250 | 0.236 | - |
0.2894 | 10300 | 0.204 | - |
0.2908 | 10350 | 0.2636 | - |
0.2922 | 10400 | 0.2562 | - |
0.2936 | 10450 | 0.2437 | - |
0.2950 | 10500 | 0.2395 | - |
0.2964 | 10550 | 0.2616 | - |
0.2979 | 10600 | 0.272 | - |
0.2993 | 10650 | 0.2637 | - |
0.3007 | 10700 | 0.2503 | - |
0.3021 | 10750 | 0.2401 | - |
0.3035 | 10800 | 0.2485 | - |
0.3049 | 10850 | 0.2521 | - |
0.3063 | 10900 | 0.256 | - |
0.3077 | 10950 | 0.2363 | - |
0.3091 | 11000 | 0.2482 | - |
0.3105 | 11050 | 0.2533 | - |
0.3119 | 11100 | 0.2598 | - |
0.3133 | 11150 | 0.2572 | - |
0.3147 | 11200 | 0.2631 | - |
0.3161 | 11250 | 0.2399 | - |
0.3175 | 11300 | 0.2509 | - |
0.3189 | 11350 | 0.2447 | - |
0.3203 | 11400 | 0.2395 | - |
0.3217 | 11450 | 0.2439 | - |
0.3231 | 11500 | 0.2497 | - |
0.3245 | 11550 | 0.2377 | - |
0.3260 | 11600 | 0.2452 | - |
0.3274 | 11650 | 0.2361 | - |
0.3288 | 11700 | 0.2431 | - |
0.3302 | 11750 | 0.2462 | - |
0.3316 | 11800 | 0.2438 | - |
0.3330 | 11850 | 0.2498 | - |
0.3344 | 11900 | 0.262 | - |
0.3358 | 11950 | 0.2451 | - |
0.3372 | 12000 | 0.251 | - |
0.3386 | 12050 | 0.2605 | - |
0.3400 | 12100 | 0.2477 | - |
0.3414 | 12150 | 0.2417 | - |
0.3428 | 12200 | 0.2566 | - |
0.3442 | 12250 | 0.2373 | - |
0.3456 | 12300 | 0.2444 | - |
0.3470 | 12350 | 0.2589 | - |
0.3484 | 12400 | 0.2491 | - |
0.3498 | 12450 | 0.2438 | - |
0.3512 | 12500 | 0.2519 | - |
0.3526 | 12550 | 0.2406 | - |
0.3541 | 12600 | 0.2472 | - |
0.3555 | 12650 | 0.2447 | - |
0.3569 | 12700 | 0.2677 | - |
0.3583 | 12750 | 0.2486 | - |
0.3597 | 12800 | 0.2585 | - |
0.3611 | 12850 | 0.2539 | - |
0.3625 | 12900 | 0.2556 | - |
0.3639 | 12950 | 0.2653 | - |
0.3653 | 13000 | 0.2583 | - |
0.3667 | 13050 | 0.2308 | - |
0.3681 | 13100 | 0.2586 | - |
0.3695 | 13150 | 0.2384 | - |
0.3709 | 13200 | 0.2645 | - |
0.3723 | 13250 | 0.2394 | - |
0.3737 | 13300 | 0.2575 | - |
0.3751 | 13350 | 0.2418 | - |
0.3765 | 13400 | 0.2414 | - |
0.3779 | 13450 | 0.2516 | - |
0.3793 | 13500 | 0.2571 | - |
0.3807 | 13550 | 0.2352 | - |
0.3822 | 13600 | 0.2584 | - |
0.3836 | 13650 | 0.2561 | - |
0.3850 | 13700 | 0.2672 | - |
0.3864 | 13750 | 0.2574 | - |
0.3878 | 13800 | 0.2398 | - |
0.3892 | 13850 | 0.2359 | - |
0.3906 | 13900 | 0.2397 | - |
0.3920 | 13950 | 0.2582 | - |
0.3934 | 14000 | 0.2468 | - |
0.3948 | 14050 | 0.2702 | - |
0.3962 | 14100 | 0.2547 | - |
0.3976 | 14150 | 0.2382 | - |
0.3990 | 14200 | 0.255 | - |
0.4004 | 14250 | 0.2382 | - |
0.4018 | 14300 | 0.2516 | - |
0.4032 | 14350 | 0.236 | - |
0.4046 | 14400 | 0.2499 | - |
0.4060 | 14450 | 0.2606 | - |
0.4074 | 14500 | 0.2514 | - |
0.4088 | 14550 | 0.2442 | - |
0.4103 | 14600 | 0.2516 | - |
0.4117 | 14650 | 0.2439 | - |
0.4131 | 14700 | 0.2547 | - |
0.4145 | 14750 | 0.2522 | - |
0.4159 | 14800 | 0.2421 | - |
0.4173 | 14850 | 0.2461 | - |
0.4187 | 14900 | 0.2663 | - |
0.4201 | 14950 | 0.259 | - |
0.4215 | 15000 | 0.2526 | - |
0.4229 | 15050 | 0.2527 | - |
0.4243 | 15100 | 0.2547 | - |
0.4257 | 15150 | 0.2696 | - |
0.4271 | 15200 | 0.2399 | - |
0.4285 | 15250 | 0.2557 | - |
0.4299 | 15300 | 0.2581 | - |
0.4313 | 15350 | 0.2402 | - |
0.4327 | 15400 | 0.2658 | - |
0.4341 | 15450 | 0.2491 | - |
0.4355 | 15500 | 0.2434 | - |
0.4369 | 15550 | 0.2511 | - |
0.4384 | 15600 | 0.2448 | - |
0.4398 | 15650 | 0.262 | - |
0.4412 | 15700 | 0.2549 | - |
0.4426 | 15750 | 0.2546 | - |
0.4440 | 15800 | 0.2444 | - |
0.4454 | 15850 | 0.2551 | - |
0.4468 | 15900 | 0.247 | - |
0.4482 | 15950 | 0.253 | - |
0.4496 | 16000 | 0.2615 | - |
0.4510 | 16050 | 0.2514 | - |
0.4524 | 16100 | 0.2587 | - |
0.4538 | 16150 | 0.2591 | - |
0.4552 | 16200 | 0.249 | - |
0.4566 | 16250 | 0.2459 | - |
0.4580 | 16300 | 0.2582 | - |
0.4594 | 16350 | 0.243 | - |
0.4608 | 16400 | 0.2493 | - |
0.4622 | 16450 | 0.2306 | - |
0.4636 | 16500 | 0.2561 | - |
0.4650 | 16550 | 0.2363 | - |
0.4664 | 16600 | 0.2412 | - |
0.4679 | 16650 | 0.2454 | - |
0.4693 | 16700 | 0.2575 | - |
0.4707 | 16750 | 0.2369 | - |
0.4721 | 16800 | 0.245 | - |
0.4735 | 16850 | 0.2591 | - |
0.4749 | 16900 | 0.2582 | - |
0.4763 | 16950 | 0.2629 | - |
0.4777 | 17000 | 0.2393 | - |
0.4791 | 17050 | 0.2563 | - |
0.4805 | 17100 | 0.2511 | - |
0.4819 | 17150 | 0.2538 | - |
0.4833 | 17200 | 0.2464 | - |
0.4847 | 17250 | 0.2511 | - |
0.4861 | 17300 | 0.244 | - |
0.4875 | 17350 | 0.2688 | - |
0.4889 | 17400 | 0.2729 | - |
0.4903 | 17450 | 0.2523 | - |
0.4917 | 17500 | 0.2507 | - |
0.4931 | 17550 | 0.2527 | - |
0.4945 | 17600 | 0.2478 | - |
0.4960 | 17650 | 0.26 | - |
0.4974 | 17700 | 0.2526 | - |
0.4988 | 17750 | 0.2549 | - |
0.5002 | 17800 | 0.2496 | - |
0.5016 | 17850 | 0.2537 | - |
0.5030 | 17900 | 0.2644 | - |
0.5044 | 17950 | 0.2633 | - |
0.5058 | 18000 | 0.2515 | - |
0.5072 | 18050 | 0.2551 | - |
0.5086 | 18100 | 0.2427 | - |
0.5100 | 18150 | 0.2615 | - |
0.5114 | 18200 | 0.2455 | - |
0.5128 | 18250 | 0.2615 | - |
0.5142 | 18300 | 0.2558 | - |
0.5156 | 18350 | 0.2483 | - |
0.5170 | 18400 | 0.2618 | - |
0.5184 | 18450 | 0.2404 | - |
0.5198 | 18500 | 0.2562 | - |
0.5212 | 18550 | 0.259 | - |
0.5226 | 18600 | 0.246 | - |
0.5241 | 18650 | 0.2529 | - |
0.5255 | 18700 | 0.2526 | - |
0.5269 | 18750 | 0.2381 | - |
0.5283 | 18800 | 0.2648 | - |
0.5297 | 18850 | 0.2628 | - |
0.5311 | 18900 | 0.2528 | - |
0.5325 | 18950 | 0.2447 | - |
0.5339 | 19000 | 0.2467 | - |
0.5353 | 19050 | 0.2487 | - |
0.5367 | 19100 | 0.2494 | - |
0.5381 | 19150 | 0.2441 | - |
0.5395 | 19200 | 0.2507 | - |
0.5409 | 19250 | 0.2494 | - |
0.5423 | 19300 | 0.2501 | - |
0.5437 | 19350 | 0.2586 | - |
0.5451 | 19400 | 0.2677 | - |
0.5465 | 19450 | 0.2558 | - |
0.5479 | 19500 | 0.2444 | - |
0.5493 | 19550 | 0.251 | - |
0.5507 | 19600 | 0.2545 | - |
0.5522 | 19650 | 0.2464 | - |
0.5536 | 19700 | 0.2565 | - |
0.5550 | 19750 | 0.2674 | - |
0.5564 | 19800 | 0.2483 | - |
0.5578 | 19850 | 0.241 | - |
0.5592 | 19900 | 0.2504 | - |
0.5606 | 19950 | 0.2655 | - |
0.5620 | 20000 | 0.2484 | - |
0.5634 | 20050 | 0.254 | - |
0.5648 | 20100 | 0.2482 | - |
0.5662 | 20150 | 0.2644 | - |
0.5676 | 20200 | 0.2694 | - |
0.5690 | 20250 | 0.258 | - |
0.5704 | 20300 | 0.2587 | - |
0.5718 | 20350 | 0.2571 | - |
0.5732 | 20400 | 0.2464 | - |
0.5746 | 20450 | 0.2531 | - |
0.5760 | 20500 | 0.2504 | - |
0.5774 | 20550 | 0.2551 | - |
0.5788 | 20600 | 0.253 | - |
0.5803 | 20650 | 0.2374 | - |
0.5817 | 20700 | 0.2405 | - |
0.5831 | 20750 | 0.2435 | - |
0.5845 | 20800 | 0.2569 | - |
0.5859 | 20850 | 0.2533 | - |
0.5873 | 20900 | 0.2508 | - |
0.5887 | 20950 | 0.2508 | - |
0.5901 | 21000 | 0.2531 | - |
0.5915 | 21050 | 0.2381 | - |
0.5929 | 21100 | 0.2009 | - |
0.5943 | 21150 | 0.0899 | - |
0.5957 | 21200 | 0.3046 | - |
0.5971 | 21250 | 0.2006 | - |
0.5985 | 21300 | 0.2289 | - |
0.5999 | 21350 | 0.1581 | - |
0.6013 | 21400 | 0.1769 | - |
0.6027 | 21450 | 0.2377 | - |
0.6041 | 21500 | 0.1988 | - |
0.6055 | 21550 | 0.2543 | - |
0.6069 | 21600 | 0.2517 | - |
0.6084 | 21650 | 0.2191 | - |
0.6098 | 21700 | 0.2803 | - |
0.6112 | 21750 | 0.2984 | - |
0.6126 | 21800 | 0.1915 | - |
0.6140 | 21850 | 0.189 | - |
0.6154 | 21900 | 0.1302 | - |
0.6168 | 21950 | 0.203 | - |
0.6182 | 22000 | 0.2038 | - |
0.6196 | 22050 | 0.134 | - |
0.6210 | 22100 | 0.1904 | - |
0.6224 | 22150 | 0.1477 | - |
0.6238 | 22200 | 0.1338 | - |
0.6252 | 22250 | 0.0709 | - |
0.6266 | 22300 | 0.0902 | - |
0.6280 | 22350 | 0.2025 | - |
0.6294 | 22400 | 0.0991 | - |
0.6308 | 22450 | 0.1321 | - |
0.6322 | 22500 | 0.1356 | - |
0.6336 | 22550 | 0.1682 | - |
0.6350 | 22600 | 0.2064 | - |
0.6365 | 22650 | 0.2 | - |
0.6379 | 22700 | 0.2105 | - |
0.6393 | 22750 | 0.2074 | - |
0.6407 | 22800 | 0.1901 | - |
0.6421 | 22850 | 0.1914 | - |
0.6435 | 22900 | 0.1831 | - |
0.6449 | 22950 | 0.1423 | - |
0.6463 | 23000 | 0.2502 | - |
0.6477 | 23050 | 0.1655 | - |
0.6491 | 23100 | 0.1585 | - |
0.6505 | 23150 | 0.2122 | - |
0.6519 | 23200 | 0.217 | - |
0.6533 | 23250 | 0.1704 | - |
0.6547 | 23300 | 0.189 | - |
0.6561 | 23350 | 0.1333 | - |
0.6575 | 23400 | 0.1863 | - |
0.6589 | 23450 | 0.2089 | - |
0.6603 | 23500 | 0.1261 | - |
0.6617 | 23550 | 0.1655 | - |
0.6631 | 23600 | 0.1721 | - |
0.6645 | 23650 | 0.083 | - |
0.6660 | 23700 | 0.1166 | - |
0.6674 | 23750 | 0.146 | - |
0.6688 | 23800 | 0.0423 | - |
0.6702 | 23850 | 0.1781 | - |
0.6716 | 23900 | 0.121 | - |
0.6730 | 23950 | 0.1624 | - |
0.6744 | 24000 | 0.1483 | - |
0.6758 | 24050 | 0.1479 | - |
0.6772 | 24100 | 0.2285 | - |
0.6786 | 24150 | 0.2084 | - |
0.6800 | 24200 | 0.12 | - |
0.6814 | 24250 | 0.115 | - |
0.6828 | 24300 | 0.1331 | - |
0.6842 | 24350 | 0.0971 | - |
0.6856 | 24400 | 0.0846 | - |
0.6870 | 24450 | 0.2254 | - |
0.6884 | 24500 | 0.1348 | - |
0.6898 | 24550 | 0.0633 | - |
0.6912 | 24600 | 0.1207 | - |
0.6926 | 24650 | 0.2109 | - |
0.6941 | 24700 | 0.0768 | - |
0.6955 | 24750 | 0.108 | - |
0.6969 | 24800 | 0.0665 | - |
0.6983 | 24850 | 0.0601 | - |
0.6997 | 24900 | 0.1922 | - |
0.7011 | 24950 | 0.1517 | - |
0.7025 | 25000 | 0.1049 | - |
0.7039 | 25050 | 0.1122 | - |
0.7053 | 25100 | 0.0973 | - |
0.7067 | 25150 | 0.1547 | - |
0.7081 | 25200 | 0.115 | - |
0.7095 | 25250 | 0.1881 | - |
0.7109 | 25300 | 0.2144 | - |
0.7123 | 25350 | 0.0567 | - |
0.7137 | 25400 | 0.0917 | - |
0.7151 | 25450 | 0.1404 | - |
0.7165 | 25500 | 0.019 | - |
0.7179 | 25550 | 0.1382 | - |
0.7193 | 25600 | 0.0727 | - |
0.7207 | 25650 | 0.1125 | - |
0.7222 | 25700 | 0.1133 | - |
0.7236 | 25750 | 0.0987 | - |
0.7250 | 25800 | 0.1915 | - |
0.7264 | 25850 | 0.09 | - |
0.7278 | 25900 | 0.1462 | - |
0.7292 | 25950 | 0.0881 | - |
0.7306 | 26000 | 0.1026 | - |
0.7320 | 26050 | 0.1079 | - |
0.7334 | 26100 | 0.1639 | - |
0.7348 | 26150 | 0.1229 | - |
0.7362 | 26200 | 0.3261 | - |
0.7376 | 26250 | 0.1426 | - |
0.7390 | 26300 | 0.0773 | - |
0.7404 | 26350 | 0.1607 | - |
0.7418 | 26400 | 0.1354 | - |
0.7432 | 26450 | 0.1512 | - |
0.7446 | 26500 | 0.1875 | - |
0.7460 | 26550 | 0.1403 | - |
0.7474 | 26600 | 0.1287 | - |
0.7488 | 26650 | 0.1892 | - |
0.7503 | 26700 | 0.166 | - |
0.7517 | 26750 | 0.2385 | - |
0.7531 | 26800 | 0.1445 | - |
0.7545 | 26850 | 0.0969 | - |
0.7559 | 26900 | 0.0948 | - |
0.7573 | 26950 | 0.0589 | - |
0.7587 | 27000 | 0.2326 | - |
0.7601 | 27050 | 0.1438 | - |
0.7615 | 27100 | 0.1032 | - |
0.7629 | 27150 | 0.0784 | - |
0.7643 | 27200 | 0.1478 | - |
0.7657 | 27250 | 0.1872 | - |
0.7671 | 27300 | 0.0672 | - |
0.7685 | 27350 | 0.0725 | - |
0.7699 | 27400 | 0.0771 | - |
0.7713 | 27450 | 0.2575 | - |
0.7727 | 27500 | 0.133 | - |
0.7741 | 27550 | 0.1222 | - |
0.7755 | 27600 | 0.1207 | - |
0.7769 | 27650 | 0.0973 | - |
0.7784 | 27700 | 0.2186 | - |
0.7798 | 27750 | 0.1648 | - |
0.7812 | 27800 | 0.1128 | - |
0.7826 | 27850 | 0.1626 | - |
0.7840 | 27900 | 0.1768 | - |
0.7854 | 27950 | 0.1806 | - |
0.7868 | 28000 | 0.1197 | - |
0.7882 | 28050 | 0.0472 | - |
0.7896 | 28100 | 0.1463 | - |
0.7910 | 28150 | 0.1707 | - |
0.7924 | 28200 | 0.0924 | - |
0.7938 | 28250 | 0.1708 | - |
0.7952 | 28300 | 0.1101 | - |
0.7966 | 28350 | 0.0867 | - |
0.7980 | 28400 | 0.1606 | - |
0.7994 | 28450 | 0.2422 | - |
0.8008 | 28500 | 0.1289 | - |
0.8022 | 28550 | 0.0513 | - |
0.8036 | 28600 | 0.1468 | - |
0.8050 | 28650 | 0.1742 | - |
0.8065 | 28700 | 0.0813 | - |
0.8079 | 28750 | 0.0916 | - |
0.8093 | 28800 | 0.0826 | - |
0.8107 | 28850 | 0.1457 | - |
0.8121 | 28900 | 0.0952 | - |
0.8135 | 28950 | 0.1376 | - |
0.8149 | 29000 | 0.06 | - |
0.8163 | 29050 | 0.1221 | - |
0.8177 | 29100 | 0.0713 | - |
0.8191 | 29150 | 0.1219 | - |
0.8205 | 29200 | 0.1051 | - |
0.8219 | 29250 | 0.1503 | - |
0.8233 | 29300 | 0.1128 | - |
0.8247 | 29350 | 0.0946 | - |
0.8261 | 29400 | 0.2115 | - |
0.8275 | 29450 | 0.1058 | - |
0.8289 | 29500 | 0.1085 | - |
0.8303 | 29550 | 0.1632 | - |
0.8317 | 29600 | 0.1022 | - |
0.8331 | 29650 | 0.136 | - |
0.8346 | 29700 | 0.1231 | - |
0.8360 | 29750 | 0.0929 | - |
0.8374 | 29800 | 0.1299 | - |
0.8388 | 29850 | 0.0693 | - |
0.8402 | 29900 | 0.0738 | - |
0.8416 | 29950 | 0.0826 | - |
0.8430 | 30000 | 0.1831 | - |
0.8444 | 30050 | 0.0962 | - |
0.8458 | 30100 | 0.0869 | - |
0.8472 | 30150 | 0.1459 | - |
0.8486 | 30200 | 0.1468 | - |
0.8500 | 30250 | 0.2132 | - |
0.8514 | 30300 | 0.1472 | - |
0.8528 | 30350 | 0.1294 | - |
0.8542 | 30400 | 0.0822 | - |
0.8556 | 30450 | 0.144 | - |
0.8570 | 30500 | 0.1216 | - |
0.8584 | 30550 | 0.1381 | - |
0.8598 | 30600 | 0.1612 | - |
0.8612 | 30650 | 0.1665 | - |
0.8627 | 30700 | 0.2035 | - |
0.8641 | 30750 | 0.136 | - |
0.8655 | 30800 | 0.1685 | - |
0.8669 | 30850 | 0.1421 | - |
0.8683 | 30900 | 0.1169 | - |
0.8697 | 30950 | 0.1799 | - |
0.8711 | 31000 | 0.2185 | - |
0.8725 | 31050 | 0.1321 | - |
0.8739 | 31100 | 0.145 | - |
0.8753 | 31150 | 0.1848 | - |
0.8767 | 31200 | 0.2173 | - |
0.8781 | 31250 | 0.2036 | - |
0.8795 | 31300 | 0.2056 | - |
0.8809 | 31350 | 0.312 | - |
0.8823 | 31400 | 0.2119 | - |
0.8837 | 31450 | 0.1875 | - |
0.8851 | 31500 | 0.2216 | - |
0.8865 | 31550 | 0.2267 | - |
0.8879 | 31600 | 0.2709 | - |
0.8893 | 31650 | 0.1868 | - |
0.8907 | 31700 | 0.1752 | - |
0.8922 | 31750 | 0.2468 | - |
0.8936 | 31800 | 0.1632 | - |
0.8950 | 31850 | 0.2483 | - |
0.8964 | 31900 | 0.1597 | - |
0.8978 | 31950 | 0.1587 | - |
0.8992 | 32000 | 0.0897 | - |
0.9006 | 32050 | 0.0764 | - |
0.9020 | 32100 | 0.1798 | - |
0.9034 | 32150 | 0.1254 | - |
0.9048 | 32200 | 0.1905 | - |
0.9062 | 32250 | 0.0714 | - |
0.9076 | 32300 | 0.1377 | - |
0.9090 | 32350 | 0.0192 | - |
0.9104 | 32400 | 0.1208 | - |
0.9118 | 32450 | 0.239 | - |
0.9132 | 32500 | 0.0965 | - |
0.9146 | 32550 | 0.1189 | - |
0.9160 | 32600 | 0.0856 | - |
0.9174 | 32650 | 0.1041 | - |
0.9188 | 32700 | 0.1107 | - |
0.9203 | 32750 | 0.1499 | - |
0.9217 | 32800 | 0.0874 | - |
0.9231 | 32850 | 0.1255 | - |
0.9245 | 32900 | 0.1099 | - |
0.9259 | 32950 | 0.1806 | - |
0.9273 | 33000 | 0.0544 | - |
0.9287 | 33050 | 0.0504 | - |
0.9301 | 33100 | 0.2441 | - |
0.9315 | 33150 | 0.0266 | - |
0.9329 | 33200 | 0.0985 | - |
0.9343 | 33250 | 0.0923 | - |
0.9357 | 33300 | 0.1054 | - |
0.9371 | 33350 | 0.0625 | - |
0.9385 | 33400 | 0.0882 | - |
0.9399 | 33450 | 0.102 | - |
0.9413 | 33500 | 0.108 | - |
0.9427 | 33550 | 0.135 | - |
0.9441 | 33600 | 0.1016 | - |
0.9455 | 33650 | 0.2008 | - |
0.9469 | 33700 | 0.0591 | - |
0.9484 | 33750 | 0.1922 | - |
0.9498 | 33800 | 0.1045 | - |
0.9512 | 33850 | 0.102 | - |
0.9526 | 33900 | 0.0634 | - |
0.9540 | 33950 | 0.0668 | - |
0.9554 | 34000 | 0.1339 | - |
0.9568 | 34050 | 0.0599 | - |
0.9582 | 34100 | 0.0623 | - |
0.9596 | 34150 | 0.1133 | - |
0.9610 | 34200 | 0.1218 | - |
0.9624 | 34250 | 0.0618 | - |
0.9638 | 34300 | 0.1062 | - |
0.9652 | 34350 | 0.0909 | - |
0.9666 | 34400 | 0.0885 | - |
0.9680 | 34450 | 0.1461 | - |
0.9694 | 34500 | 0.0254 | - |
0.9708 | 34550 | 0.0697 | - |
0.9722 | 34600 | 0.016 | - |
0.9736 | 34650 | 0.1524 | - |
0.9750 | 34700 | 0.1468 | - |
0.9765 | 34750 | 0.1497 | - |
0.9779 | 34800 | 0.0785 | - |
0.9793 | 34850 | 0.0645 | - |
0.9807 | 34900 | 0.1357 | - |
0.9821 | 34950 | 0.1469 | - |
0.9835 | 35000 | 0.2356 | - |
0.9849 | 35050 | 0.018 | - |
0.9863 | 35100 | 0.1534 | - |
0.9877 | 35150 | 0.14 | - |
0.9891 | 35200 | 0.1001 | - |
0.9905 | 35250 | 0.0614 | - |
0.9919 | 35300 | 0.1407 | - |
0.9933 | 35350 | 0.1104 | - |
0.9947 | 35400 | 0.1477 | - |
0.9961 | 35450 | 0.1279 | - |
0.9975 | 35500 | 0.0957 | - |
0.9989 | 35550 | 0.0579 | - |
1.0 | 35588 | - | 0.1207 |
- The bold row denotes the saved checkpoint.
Framework Versions
- Python: 3.11.9
- SetFit: 1.1.0.dev0
- Sentence Transformers: 3.0.1
- Transformers: 4.44.2
- PyTorch: 2.4.0+cu121
- Datasets: 2.21.0
- Tokenizers: 0.19.1
Citation
BibTeX
@article{https://doi.org/10.48550/arxiv.2209.11055,
doi = {10.48550/ARXIV.2209.11055},
url = {https://arxiv.org/abs/2209.11055},
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Efficient Few-Shot Learning Without Prompts},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}
- Downloads last month
- 4
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for nazhan/bge-large-en-v1.5-brahmaputra-iter-9-1-epoch
Base model
BAAI/bge-large-en-v1.5