update model card README.md

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	---
	license: mit
	tags:
	- generated_from_trainer
	datasets:
	- crows_pairs
	metrics:
	- accuracy
	model-index:
	- name: gpt2_crows_pairs_finetuned
	results:
	- task:
	name: Text Classification
	type: text-classification
	dataset:
	name: crows_pairs
	type: crows_pairs
	config: crows_pairs
	split: test
	args: crows_pairs
	metrics:
	- name: Accuracy
	type: accuracy
	value: 0.7781456953642384
	---

	<!-- This model card has been generated automatically according to the information the Trainer had access to. You
	should probably proofread and complete it, then remove this comment. -->

	# gpt2_crows_pairs_finetuned

	This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the crows_pairs dataset.
	It achieves the following results on the evaluation set:
	- Loss: 2.0946
	- Accuracy: 0.7781
	- Tp: 0.3444
	- Tn: 0.4338
	- Fp: 0.1159
	- Fn: 0.1060

	## Model description

	More information needed

	## Intended uses & limitations

	More information needed

	## Training and evaluation data

	More information needed

	## Training procedure

	### Training hyperparameters

	The following hyperparameters were used during training:
	- learning_rate: 5e-05
	- train_batch_size: 64
	- eval_batch_size: 64
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- num_epochs: 50

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| Tp \| Tn \| Fp \| Fn \|
	\|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:------:\|:------:\|:------:\|:------:\|
	\| 0.7371 \| 1.05 \| 20 \| 0.7345 \| 0.4669 \| 0.4305 \| 0.0364 \| 0.5132 \| 0.0199 \|
	\| 0.6794 \| 2.11 \| 40 \| 0.6829 \| 0.5397 \| 0.3013 \| 0.2384 \| 0.3113 \| 0.1490 \|
	\| 0.5972 \| 3.16 \| 60 \| 0.6602 \| 0.6291 \| 0.3411 \| 0.2881 \| 0.2616 \| 0.1093 \|
	\| 0.4691 \| 4.21 \| 80 \| 0.6568 \| 0.6788 \| 0.3742 \| 0.3046 \| 0.2450 \| 0.0762 \|
	\| 0.3645 \| 5.26 \| 100 \| 0.5872 \| 0.7252 \| 0.2815 \| 0.4437 \| 0.1060 \| 0.1689 \|
	\| 0.2645 \| 6.32 \| 120 \| 0.6835 \| 0.7185 \| 0.2318 \| 0.4868 \| 0.0629 \| 0.2185 \|
	\| 0.1698 \| 7.37 \| 140 \| 0.7757 \| 0.7483 \| 0.2914 \| 0.4570 \| 0.0927 \| 0.1589 \|
	\| 0.1386 \| 8.42 \| 160 \| 0.7445 \| 0.7417 \| 0.2881 \| 0.4536 \| 0.0960 \| 0.1623 \|
	\| 0.077 \| 9.47 \| 180 \| 1.0591 \| 0.7252 \| 0.3642 \| 0.3609 \| 0.1887 \| 0.0861 \|
	\| 0.0836 \| 10.53 \| 200 \| 1.0908 \| 0.7185 \| 0.2649 \| 0.4536 \| 0.0960 \| 0.1854 \|
	\| 0.0485 \| 11.58 \| 220 \| 1.2155 \| 0.7450 \| 0.3709 \| 0.3742 \| 0.1755 \| 0.0795 \|
	\| 0.0298 \| 12.63 \| 240 \| 1.1973 \| 0.7417 \| 0.3245 \| 0.4172 \| 0.1325 \| 0.1258 \|
	\| 0.0444 \| 13.68 \| 260 \| 1.4213 \| 0.7384 \| 0.3675 \| 0.3709 \| 0.1788 \| 0.0828 \|
	\| 0.0215 \| 14.74 \| 280 \| 1.4907 \| 0.7450 \| 0.3278 \| 0.4172 \| 0.1325 \| 0.1225 \|
	\| 0.0483 \| 15.79 \| 300 \| 1.5485 \| 0.7583 \| 0.2781 \| 0.4801 \| 0.0695 \| 0.1722 \|
	\| 0.0129 \| 16.84 \| 320 \| 1.7145 \| 0.7550 \| 0.2748 \| 0.4801 \| 0.0695 \| 0.1755 \|
	\| 0.0525 \| 17.89 \| 340 \| 1.7827 \| 0.7550 \| 0.3642 \| 0.3907 \| 0.1589 \| 0.0861 \|
	\| 0.0074 \| 18.95 \| 360 \| 1.6230 \| 0.7682 \| 0.2980 \| 0.4702 \| 0.0795 \| 0.1523 \|
	\| 0.004 \| 20.0 \| 380 \| 1.8522 \| 0.7384 \| 0.3444 \| 0.3940 \| 0.1556 \| 0.1060 \|
	\| 0.0067 \| 21.05 \| 400 \| 1.8479 \| 0.7616 \| 0.3046 \| 0.4570 \| 0.0927 \| 0.1457 \|
	\| 0.001 \| 22.11 \| 420 \| 1.9830 \| 0.7682 \| 0.2947 \| 0.4735 \| 0.0762 \| 0.1556 \|
	\| 0.01 \| 23.16 \| 440 \| 1.9412 \| 0.7715 \| 0.3113 \| 0.4603 \| 0.0894 \| 0.1391 \|
	\| 0.0048 \| 24.21 \| 460 \| 2.0075 \| 0.7649 \| 0.3510 \| 0.4139 \| 0.1358 \| 0.0993 \|
	\| 0.0025 \| 25.26 \| 480 \| 2.0912 \| 0.7649 \| 0.2980 \| 0.4669 \| 0.0828 \| 0.1523 \|
	\| 0.0013 \| 26.32 \| 500 \| 2.1548 \| 0.7715 \| 0.3444 \| 0.4272 \| 0.1225 \| 0.1060 \|
	\| 0.0041 \| 27.37 \| 520 \| 2.1337 \| 0.7682 \| 0.3543 \| 0.4139 \| 0.1358 \| 0.0960 \|
	\| 0.0005 \| 28.42 \| 540 \| 2.1242 \| 0.7550 \| 0.3576 \| 0.3974 \| 0.1523 \| 0.0927 \|
	\| 0.0124 \| 29.47 \| 560 \| 2.1297 \| 0.7583 \| 0.3642 \| 0.3940 \| 0.1556 \| 0.0861 \|
	\| 0.0104 \| 30.53 \| 580 \| 2.0057 \| 0.7583 \| 0.3179 \| 0.4404 \| 0.1093 \| 0.1325 \|
	\| 0.0156 \| 31.58 \| 600 \| 2.0365 \| 0.7483 \| 0.2881 \| 0.4603 \| 0.0894 \| 0.1623 \|
	\| 0.0003 \| 32.63 \| 620 \| 1.9614 \| 0.7649 \| 0.3212 \| 0.4437 \| 0.1060 \| 0.1291 \|
	\| 0.0029 \| 33.68 \| 640 \| 1.9658 \| 0.7682 \| 0.3245 \| 0.4437 \| 0.1060 \| 0.1258 \|
	\| 0.0001 \| 34.74 \| 660 \| 1.9913 \| 0.7649 \| 0.3013 \| 0.4636 \| 0.0861 \| 0.1490 \|
	\| 0.0001 \| 35.79 \| 680 \| 2.0039 \| 0.7649 \| 0.3013 \| 0.4636 \| 0.0861 \| 0.1490 \|
	\| 0.0004 \| 36.84 \| 700 \| 1.9657 \| 0.7715 \| 0.3146 \| 0.4570 \| 0.0927 \| 0.1358 \|
	\| 0.0003 \| 37.89 \| 720 \| 1.9787 \| 0.7748 \| 0.3245 \| 0.4503 \| 0.0993 \| 0.1258 \|
	\| 0.0007 \| 38.95 \| 740 \| 1.9888 \| 0.7781 \| 0.3377 \| 0.4404 \| 0.1093 \| 0.1126 \|
	\| 0.0002 \| 40.0 \| 760 \| 2.0293 \| 0.7682 \| 0.3477 \| 0.4205 \| 0.1291 \| 0.1026 \|
	\| 0.0002 \| 41.05 \| 780 \| 1.9914 \| 0.7781 \| 0.3245 \| 0.4536 \| 0.0960 \| 0.1258 \|
	\| 0.0003 \| 42.11 \| 800 \| 2.0444 \| 0.7583 \| 0.2914 \| 0.4669 \| 0.0828 \| 0.1589 \|
	\| 0.0072 \| 43.16 \| 820 \| 2.0247 \| 0.7649 \| 0.3278 \| 0.4371 \| 0.1126 \| 0.1225 \|
	\| 0.0001 \| 44.21 \| 840 \| 2.0398 \| 0.7682 \| 0.3278 \| 0.4404 \| 0.1093 \| 0.1225 \|
	\| 0.0001 \| 45.26 \| 860 \| 2.0358 \| 0.7682 \| 0.3278 \| 0.4404 \| 0.1093 \| 0.1225 \|
	\| 0.0011 \| 46.32 \| 880 \| 2.0432 \| 0.7682 \| 0.3278 \| 0.4404 \| 0.1093 \| 0.1225 \|
	\| 0.0001 \| 47.37 \| 900 \| 2.0923 \| 0.7781 \| 0.3444 \| 0.4338 \| 0.1159 \| 0.1060 \|
	\| 0.0 \| 48.42 \| 920 \| 2.0975 \| 0.7781 \| 0.3444 \| 0.4338 \| 0.1159 \| 0.1060 \|
	\| 0.0002 \| 49.47 \| 940 \| 2.0946 \| 0.7781 \| 0.3444 \| 0.4338 \| 0.1159 \| 0.1060 \|


	### Framework versions

	- Transformers 4.26.1
	- Pytorch 1.13.1
	- Datasets 2.10.1
	- Tokenizers 0.13.2