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	---
	license: apache-2.0
	tags:
	- generated_from_trainer
	datasets:
	- super_glue
	metrics:
	- accuracy
	model-index:
	- name: 2_4e-3_1_0.1
	results: []
	---

	<!-- 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. -->

	# 2_4e-3_1_0.1

	This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the super_glue dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.5293
	- Accuracy: 0.7272

	## 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: 0.004
	- train_batch_size: 16
	- eval_batch_size: 8
	- seed: 11
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- num_epochs: 60.0

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:--------:\|
	\| 0.8756 \| 1.0 \| 590 \| 0.9984 \| 0.6211 \|
	\| 0.8309 \| 2.0 \| 1180 \| 0.7494 \| 0.6217 \|
	\| 0.8162 \| 3.0 \| 1770 \| 0.8910 \| 0.3826 \|
	\| 0.8025 \| 4.0 \| 2360 \| 0.6504 \| 0.6028 \|
	\| 0.8059 \| 5.0 \| 2950 \| 0.6535 \| 0.5945 \|
	\| 0.768 \| 6.0 \| 3540 \| 0.6293 \| 0.6291 \|
	\| 0.7423 \| 7.0 \| 4130 \| 0.9356 \| 0.4339 \|
	\| 0.7272 \| 8.0 \| 4720 \| 0.7985 \| 0.6220 \|
	\| 0.7076 \| 9.0 \| 5310 \| 0.6240 \| 0.6541 \|
	\| 0.6803 \| 10.0 \| 5900 \| 0.6284 \| 0.6639 \|
	\| 0.6637 \| 11.0 \| 6490 \| 0.6013 \| 0.6691 \|
	\| 0.6217 \| 12.0 \| 7080 \| 0.5783 \| 0.6725 \|
	\| 0.6169 \| 13.0 \| 7670 \| 0.5657 \| 0.6841 \|
	\| 0.5962 \| 14.0 \| 8260 \| 0.6273 \| 0.6618 \|
	\| 0.5937 \| 15.0 \| 8850 \| 0.5982 \| 0.6725 \|
	\| 0.5811 \| 16.0 \| 9440 \| 0.6778 \| 0.5997 \|
	\| 0.5534 \| 17.0 \| 10030 \| 0.5478 \| 0.7028 \|
	\| 0.5641 \| 18.0 \| 10620 \| 0.5615 \| 0.7034 \|
	\| 0.5588 \| 19.0 \| 11210 \| 0.5467 \| 0.7076 \|
	\| 0.5611 \| 20.0 \| 11800 \| 0.5505 \| 0.7058 \|
	\| 0.5423 \| 21.0 \| 12390 \| 0.5617 \| 0.7086 \|
	\| 0.5372 \| 22.0 \| 12980 \| 0.5483 \| 0.7003 \|
	\| 0.5387 \| 23.0 \| 13570 \| 0.5560 \| 0.7113 \|
	\| 0.5274 \| 24.0 \| 14160 \| 0.5278 \| 0.7131 \|
	\| 0.5242 \| 25.0 \| 14750 \| 0.5377 \| 0.7150 \|
	\| 0.5256 \| 26.0 \| 15340 \| 0.5796 \| 0.6856 \|
	\| 0.5203 \| 27.0 \| 15930 \| 0.5456 \| 0.6976 \|
	\| 0.5087 \| 28.0 \| 16520 \| 0.5365 \| 0.7199 \|
	\| 0.5127 \| 29.0 \| 17110 \| 0.5419 \| 0.7049 \|
	\| 0.5005 \| 30.0 \| 17700 \| 0.5417 \| 0.7257 \|
	\| 0.5008 \| 31.0 \| 18290 \| 0.5257 \| 0.7116 \|
	\| 0.4959 \| 32.0 \| 18880 \| 0.5463 \| 0.7232 \|
	\| 0.4931 \| 33.0 \| 19470 \| 0.5251 \| 0.7260 \|
	\| 0.4849 \| 34.0 \| 20060 \| 0.5282 \| 0.7217 \|
	\| 0.4733 \| 35.0 \| 20650 \| 0.5296 \| 0.7199 \|
	\| 0.4842 \| 36.0 \| 21240 \| 0.5230 \| 0.7229 \|
	\| 0.4811 \| 37.0 \| 21830 \| 0.5264 \| 0.7232 \|
	\| 0.4683 \| 38.0 \| 22420 \| 0.5518 \| 0.7058 \|
	\| 0.4692 \| 39.0 \| 23010 \| 0.5256 \| 0.7300 \|
	\| 0.4621 \| 40.0 \| 23600 \| 0.5292 \| 0.7303 \|
	\| 0.4624 \| 41.0 \| 24190 \| 0.5467 \| 0.7110 \|
	\| 0.4618 \| 42.0 \| 24780 \| 0.5189 \| 0.7324 \|
	\| 0.465 \| 43.0 \| 25370 \| 0.5285 \| 0.7330 \|
	\| 0.453 \| 44.0 \| 25960 \| 0.5577 \| 0.7113 \|
	\| 0.4533 \| 45.0 \| 26550 \| 0.5170 \| 0.7343 \|
	\| 0.4524 \| 46.0 \| 27140 \| 0.5219 \| 0.7223 \|
	\| 0.4454 \| 47.0 \| 27730 \| 0.5367 \| 0.7257 \|
	\| 0.4401 \| 48.0 \| 28320 \| 0.5251 \| 0.7339 \|
	\| 0.4547 \| 49.0 \| 28910 \| 0.5300 \| 0.7254 \|
	\| 0.4374 \| 50.0 \| 29500 \| 0.5318 \| 0.7278 \|
	\| 0.444 \| 51.0 \| 30090 \| 0.5317 \| 0.7239 \|
	\| 0.4363 \| 52.0 \| 30680 \| 0.5309 \| 0.7306 \|
	\| 0.4381 \| 53.0 \| 31270 \| 0.5206 \| 0.7312 \|
	\| 0.4314 \| 54.0 \| 31860 \| 0.5283 \| 0.7269 \|
	\| 0.4334 \| 55.0 \| 32450 \| 0.5254 \| 0.7278 \|
	\| 0.43 \| 56.0 \| 33040 \| 0.5317 \| 0.7278 \|
	\| 0.4194 \| 57.0 \| 33630 \| 0.5261 \| 0.7272 \|
	\| 0.4341 \| 58.0 \| 34220 \| 0.5266 \| 0.7300 \|
	\| 0.4243 \| 59.0 \| 34810 \| 0.5269 \| 0.7275 \|
	\| 0.4191 \| 60.0 \| 35400 \| 0.5293 \| 0.7272 \|


	### Framework versions

	- Transformers 4.30.0
	- Pytorch 2.0.1+cu117
	- Datasets 2.14.4
	- Tokenizers 0.13.3

	---
	license: apache-2.0
	tags:
	- generated_from_trainer
	datasets:
	- super_glue
	metrics:
	- accuracy
	model-index:
	- name: 2_4e-3_1_0.1
	results: []
	---

	<!-- 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. -->

	# 2_4e-3_1_0.1

	This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the super_glue dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.5293
	- Accuracy: 0.7272

	## 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: 0.004
	- train_batch_size: 16
	- eval_batch_size: 8
	- seed: 11
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- num_epochs: 60.0

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:--------:\|
	\| 0.8756 \| 1.0 \| 590 \| 0.9984 \| 0.6211 \|
	\| 0.8309 \| 2.0 \| 1180 \| 0.7494 \| 0.6217 \|
	\| 0.8162 \| 3.0 \| 1770 \| 0.8910 \| 0.3826 \|
	\| 0.8025 \| 4.0 \| 2360 \| 0.6504 \| 0.6028 \|
	\| 0.8059 \| 5.0 \| 2950 \| 0.6535 \| 0.5945 \|
	\| 0.768 \| 6.0 \| 3540 \| 0.6293 \| 0.6291 \|
	\| 0.7423 \| 7.0 \| 4130 \| 0.9356 \| 0.4339 \|
	\| 0.7272 \| 8.0 \| 4720 \| 0.7985 \| 0.6220 \|
	\| 0.7076 \| 9.0 \| 5310 \| 0.6240 \| 0.6541 \|
	\| 0.6803 \| 10.0 \| 5900 \| 0.6284 \| 0.6639 \|
	\| 0.6637 \| 11.0 \| 6490 \| 0.6013 \| 0.6691 \|
	\| 0.6217 \| 12.0 \| 7080 \| 0.5783 \| 0.6725 \|
	\| 0.6169 \| 13.0 \| 7670 \| 0.5657 \| 0.6841 \|
	\| 0.5962 \| 14.0 \| 8260 \| 0.6273 \| 0.6618 \|
	\| 0.5937 \| 15.0 \| 8850 \| 0.5982 \| 0.6725 \|
	\| 0.5811 \| 16.0 \| 9440 \| 0.6778 \| 0.5997 \|
	\| 0.5534 \| 17.0 \| 10030 \| 0.5478 \| 0.7028 \|
	\| 0.5641 \| 18.0 \| 10620 \| 0.5615 \| 0.7034 \|
	\| 0.5588 \| 19.0 \| 11210 \| 0.5467 \| 0.7076 \|
	\| 0.5611 \| 20.0 \| 11800 \| 0.5505 \| 0.7058 \|
	\| 0.5423 \| 21.0 \| 12390 \| 0.5617 \| 0.7086 \|
	\| 0.5372 \| 22.0 \| 12980 \| 0.5483 \| 0.7003 \|
	\| 0.5387 \| 23.0 \| 13570 \| 0.5560 \| 0.7113 \|
	\| 0.5274 \| 24.0 \| 14160 \| 0.5278 \| 0.7131 \|
	\| 0.5242 \| 25.0 \| 14750 \| 0.5377 \| 0.7150 \|
	\| 0.5256 \| 26.0 \| 15340 \| 0.5796 \| 0.6856 \|
	\| 0.5203 \| 27.0 \| 15930 \| 0.5456 \| 0.6976 \|
	\| 0.5087 \| 28.0 \| 16520 \| 0.5365 \| 0.7199 \|
	\| 0.5127 \| 29.0 \| 17110 \| 0.5419 \| 0.7049 \|
	\| 0.5005 \| 30.0 \| 17700 \| 0.5417 \| 0.7257 \|
	\| 0.5008 \| 31.0 \| 18290 \| 0.5257 \| 0.7116 \|
	\| 0.4959 \| 32.0 \| 18880 \| 0.5463 \| 0.7232 \|
	\| 0.4931 \| 33.0 \| 19470 \| 0.5251 \| 0.7260 \|
	\| 0.4849 \| 34.0 \| 20060 \| 0.5282 \| 0.7217 \|
	\| 0.4733 \| 35.0 \| 20650 \| 0.5296 \| 0.7199 \|
	\| 0.4842 \| 36.0 \| 21240 \| 0.5230 \| 0.7229 \|
	\| 0.4811 \| 37.0 \| 21830 \| 0.5264 \| 0.7232 \|
	\| 0.4683 \| 38.0 \| 22420 \| 0.5518 \| 0.7058 \|
	\| 0.4692 \| 39.0 \| 23010 \| 0.5256 \| 0.7300 \|
	\| 0.4621 \| 40.0 \| 23600 \| 0.5292 \| 0.7303 \|
	\| 0.4624 \| 41.0 \| 24190 \| 0.5467 \| 0.7110 \|
	\| 0.4618 \| 42.0 \| 24780 \| 0.5189 \| 0.7324 \|
	\| 0.465 \| 43.0 \| 25370 \| 0.5285 \| 0.7330 \|
	\| 0.453 \| 44.0 \| 25960 \| 0.5577 \| 0.7113 \|
	\| 0.4533 \| 45.0 \| 26550 \| 0.5170 \| 0.7343 \|
	\| 0.4524 \| 46.0 \| 27140 \| 0.5219 \| 0.7223 \|
	\| 0.4454 \| 47.0 \| 27730 \| 0.5367 \| 0.7257 \|
	\| 0.4401 \| 48.0 \| 28320 \| 0.5251 \| 0.7339 \|
	\| 0.4547 \| 49.0 \| 28910 \| 0.5300 \| 0.7254 \|
	\| 0.4374 \| 50.0 \| 29500 \| 0.5318 \| 0.7278 \|
	\| 0.444 \| 51.0 \| 30090 \| 0.5317 \| 0.7239 \|
	\| 0.4363 \| 52.0 \| 30680 \| 0.5309 \| 0.7306 \|
	\| 0.4381 \| 53.0 \| 31270 \| 0.5206 \| 0.7312 \|
	\| 0.4314 \| 54.0 \| 31860 \| 0.5283 \| 0.7269 \|
	\| 0.4334 \| 55.0 \| 32450 \| 0.5254 \| 0.7278 \|
	\| 0.43 \| 56.0 \| 33040 \| 0.5317 \| 0.7278 \|
	\| 0.4194 \| 57.0 \| 33630 \| 0.5261 \| 0.7272 \|
	\| 0.4341 \| 58.0 \| 34220 \| 0.5266 \| 0.7300 \|
	\| 0.4243 \| 59.0 \| 34810 \| 0.5269 \| 0.7275 \|
	\| 0.4191 \| 60.0 \| 35400 \| 0.5293 \| 0.7272 \|


	### Framework versions

	- Transformers 4.30.0
	- Pytorch 2.0.1+cu117
	- Datasets 2.14.4
	- Tokenizers 0.13.3