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	---
	license: apache-2.0
	base_model: alignment-handbook/zephyr-7b-sft-full
	tags:
	- generated_from_trainer
	model-index:
	- name: zephyr-7b-dpo-full-beta-0.083
	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. -->

	# zephyr-7b-dpo-full-beta-0.083

	This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the None dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.6981
	- Rewards/chosen: -5.0359
	- Rewards/rejected: -8.8405
	- Rewards/accuracies: 0.7930
	- Rewards/margins: 3.8046
	- Logps/rejected: -345.7131
	- Logps/chosen: -343.6803
	- Logits/rejected: -2.5377
	- Logits/chosen: -2.6128

	## 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-07
	- train_batch_size: 8
	- eval_batch_size: 16
	- seed: 42
	- distributed_type: multi-GPU
	- num_devices: 4
	- total_train_batch_size: 32
	- total_eval_batch_size: 64
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- lr_scheduler_warmup_ratio: 0.1
	- num_epochs: 3

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \|
	\|:-------------:\|:-----:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\|
	\| 0.6224 \| 0.05 \| 100 \| 0.6037 \| 0.0537 \| -0.1781 \| 0.7129 \| 0.2318 \| -241.3471 \| -282.3603 \| -3.0281 \| -3.0500 \|
	\| 0.4992 \| 0.1 \| 200 \| 0.5157 \| 0.0022 \| -0.7572 \| 0.7520 \| 0.7594 \| -248.3236 \| -282.9802 \| -2.9768 \| -3.0038 \|
	\| 0.5334 \| 0.15 \| 300 \| 0.4983 \| -0.1003 \| -1.0616 \| 0.7695 \| 0.9613 \| -251.9916 \| -284.2161 \| -3.0036 \| -3.0272 \|
	\| 0.5479 \| 0.21 \| 400 \| 0.4918 \| -0.1860 \| -1.2242 \| 0.7656 \| 1.0381 \| -253.9503 \| -285.2488 \| -3.1264 \| -3.1487 \|
	\| 0.531 \| 0.26 \| 500 \| 0.4929 \| -0.4703 \| -1.5754 \| 0.7559 \| 1.1051 \| -258.1821 \| -288.6731 \| -3.0860 \| -3.1247 \|
	\| 0.486 \| 0.31 \| 600 \| 0.5096 \| -0.3559 \| -1.4424 \| 0.7285 \| 1.0865 \| -256.5800 \| -287.2958 \| -3.0519 \| -3.0920 \|
	\| 0.4858 \| 0.36 \| 700 \| 0.5079 \| -0.6230 \| -1.9605 \| 0.7812 \| 1.3375 \| -262.8217 \| -290.5133 \| -2.9452 \| -2.9906 \|
	\| 0.4844 \| 0.41 \| 800 \| 0.4998 \| -0.7197 \| -2.1472 \| 0.7559 \| 1.4275 \| -265.0713 \| -291.6787 \| -2.7574 \| -2.7909 \|
	\| 0.4999 \| 0.46 \| 900 \| 0.4983 \| -0.5951 \| -1.8837 \| 0.7637 \| 1.2886 \| -261.8963 \| -290.1770 \| -2.9454 \| -2.9806 \|
	\| 0.45 \| 0.52 \| 1000 \| 0.4916 \| -0.6703 \| -2.2026 \| 0.7676 \| 1.5323 \| -265.7383 \| -291.0830 \| -2.9158 \| -2.9444 \|
	\| 0.5239 \| 0.57 \| 1100 \| 0.4848 \| -0.8068 \| -2.1600 \| 0.7695 \| 1.3532 \| -265.2255 \| -292.7281 \| -2.8454 \| -2.8788 \|
	\| 0.4766 \| 0.62 \| 1200 \| 0.4974 \| -0.5971 \| -1.8739 \| 0.7441 \| 1.2769 \| -261.7786 \| -290.2007 \| -2.8189 \| -2.8673 \|
	\| 0.497 \| 0.67 \| 1300 \| 0.5048 \| -1.0382 \| -2.4646 \| 0.7266 \| 1.4264 \| -268.8953 \| -295.5161 \| -2.8081 \| -2.8508 \|
	\| 0.5281 \| 0.72 \| 1400 \| 0.5003 \| -1.0137 \| -2.1947 \| 0.7559 \| 1.1810 \| -265.6436 \| -295.2208 \| -2.7945 \| -2.8255 \|
	\| 0.4428 \| 0.77 \| 1500 \| 0.4851 \| -0.8809 \| -2.3005 \| 0.7598 \| 1.4196 \| -266.9182 \| -293.6202 \| -2.7815 \| -2.8139 \|
	\| 0.5192 \| 0.83 \| 1600 \| 0.4758 \| -0.9091 \| -2.3825 \| 0.7539 \| 1.4735 \| -267.9066 \| -293.9598 \| -2.7394 \| -2.7728 \|
	\| 0.533 \| 0.88 \| 1700 \| 0.4753 \| -0.8150 \| -2.1835 \| 0.7676 \| 1.3685 \| -265.5082 \| -292.8266 \| -2.8005 \| -2.8330 \|
	\| 0.5803 \| 0.93 \| 1800 \| 0.4854 \| -0.6814 \| -2.0356 \| 0.75 \| 1.3542 \| -263.7262 \| -291.2166 \| -2.7118 \| -2.7542 \|
	\| 0.4714 \| 0.98 \| 1900 \| 0.4855 \| -0.7688 \| -2.1323 \| 0.7559 \| 1.3634 \| -264.8912 \| -292.2704 \| -2.6864 \| -2.7287 \|
	\| 0.0702 \| 1.03 \| 2000 \| 0.4988 \| -1.4916 \| -3.5339 \| 0.7793 \| 2.0423 \| -281.7779 \| -300.9782 \| -2.6172 \| -2.6670 \|
	\| 0.0732 \| 1.08 \| 2100 \| 0.5188 \| -1.6274 \| -3.8428 \| 0.7793 \| 2.2154 \| -285.4998 \| -302.6147 \| -2.6360 \| -2.6881 \|
	\| 0.077 \| 1.14 \| 2200 \| 0.5274 \| -2.1510 \| -4.2855 \| 0.7812 \| 2.1345 \| -290.8334 \| -308.9228 \| -2.7288 \| -2.7823 \|
	\| 0.0673 \| 1.19 \| 2300 \| 0.5169 \| -1.7308 \| -3.9343 \| 0.7832 \| 2.2035 \| -286.6026 \| -303.8600 \| -2.6971 \| -2.7569 \|
	\| 0.1039 \| 1.24 \| 2400 \| 0.5115 \| -1.7156 \| -3.7812 \| 0.7715 \| 2.0655 \| -284.7573 \| -303.6773 \| -2.6974 \| -2.7420 \|
	\| 0.0961 \| 1.29 \| 2500 \| 0.5290 \| -2.3303 \| -4.5271 \| 0.7734 \| 2.1968 \| -293.7446 \| -311.0832 \| -2.7071 \| -2.7485 \|
	\| 0.1269 \| 1.34 \| 2600 \| 0.5061 \| -1.8237 \| -3.7726 \| 0.7695 \| 1.9490 \| -284.6546 \| -304.9791 \| -2.7066 \| -2.7432 \|
	\| 0.0959 \| 1.39 \| 2700 \| 0.5066 \| -1.8437 \| -3.9127 \| 0.7793 \| 2.0690 \| -286.3417 \| -305.2205 \| -2.7061 \| -2.7584 \|
	\| 0.1009 \| 1.45 \| 2800 \| 0.5241 \| -2.4471 \| -4.6093 \| 0.7852 \| 2.1622 \| -294.7356 \| -312.4907 \| -2.6836 \| -2.7338 \|
	\| 0.0917 \| 1.5 \| 2900 \| 0.5350 \| -2.4581 \| -4.5278 \| 0.75 \| 2.0697 \| -293.7532 \| -312.6228 \| -2.7069 \| -2.7588 \|
	\| 0.0693 \| 1.55 \| 3000 \| 0.5371 \| -2.3570 \| -4.5566 \| 0.7578 \| 2.1996 \| -294.1000 \| -311.4046 \| -2.7179 \| -2.7642 \|
	\| 0.0861 \| 1.6 \| 3100 \| 0.5141 \| -2.1264 \| -4.2158 \| 0.7754 \| 2.0894 \| -289.9940 \| -308.6270 \| -2.7429 \| -2.8104 \|
	\| 0.0851 \| 1.65 \| 3200 \| 0.5175 \| -1.9273 \| -4.0951 \| 0.7695 \| 2.1678 \| -288.5394 \| -306.2276 \| -2.6925 \| -2.7584 \|
	\| 0.0837 \| 1.7 \| 3300 \| 0.5354 \| -2.0696 \| -4.3985 \| 0.7637 \| 2.3289 \| -292.1949 \| -307.9421 \| -2.6726 \| -2.7440 \|
	\| 0.056 \| 1.76 \| 3400 \| 0.5596 \| -2.7840 \| -5.3198 \| 0.7734 \| 2.5358 \| -303.2956 \| -316.5497 \| -2.6498 \| -2.7202 \|
	\| 0.0689 \| 1.81 \| 3500 \| 0.5348 \| -2.3076 \| -4.5718 \| 0.7812 \| 2.2642 \| -294.2832 \| -310.8093 \| -2.7109 \| -2.7732 \|
	\| 0.0934 \| 1.86 \| 3600 \| 0.5539 \| -2.6736 \| -5.0332 \| 0.7734 \| 2.3596 \| -299.8421 \| -315.2191 \| -2.6534 \| -2.7272 \|
	\| 0.0694 \| 1.91 \| 3700 \| 0.5426 \| -2.6655 \| -4.9512 \| 0.7695 \| 2.2857 \| -298.8542 \| -315.1215 \| -2.6730 \| -2.7433 \|
	\| 0.1267 \| 1.96 \| 3800 \| 0.5620 \| -2.8767 \| -5.0299 \| 0.7910 \| 2.1531 \| -299.8019 \| -317.6664 \| -2.6778 \| -2.7430 \|
	\| 0.024 \| 2.01 \| 3900 \| 0.5618 \| -2.9659 \| -5.5768 \| 0.7832 \| 2.6109 \| -306.3921 \| -318.7414 \| -2.6526 \| -2.7240 \|
	\| 0.0171 \| 2.07 \| 4000 \| 0.6117 \| -3.6584 \| -6.6949 \| 0.7793 \| 3.0364 \| -319.8622 \| -327.0849 \| -2.6017 \| -2.6789 \|
	\| 0.0112 \| 2.12 \| 4100 \| 0.6536 \| -3.8851 \| -7.0803 \| 0.7734 \| 3.1953 \| -324.5066 \| -329.8155 \| -2.6007 \| -2.6772 \|
	\| 0.0123 \| 2.17 \| 4200 \| 0.6296 \| -3.5916 \| -6.6239 \| 0.7734 \| 3.0323 \| -319.0072 \| -326.2793 \| -2.6019 \| -2.6741 \|
	\| 0.0135 \| 2.22 \| 4300 \| 0.6245 \| -3.6464 \| -6.7754 \| 0.7832 \| 3.1289 \| -320.8321 \| -326.9404 \| -2.5877 \| -2.6570 \|
	\| 0.0147 \| 2.27 \| 4400 \| 0.6659 \| -4.4576 \| -7.8315 \| 0.7832 \| 3.3739 \| -333.5571 \| -336.7133 \| -2.5400 \| -2.6114 \|
	\| 0.0193 \| 2.32 \| 4500 \| 0.6365 \| -4.0338 \| -7.4212 \| 0.7832 \| 3.3874 \| -328.6134 \| -331.6075 \| -2.4882 \| -2.5622 \|
	\| 0.0141 \| 2.37 \| 4600 \| 0.6966 \| -4.9177 \| -8.5470 \| 0.7930 \| 3.6293 \| -342.1769 \| -342.2570 \| -2.4891 \| -2.5649 \|
	\| 0.0126 \| 2.43 \| 4700 \| 0.6972 \| -4.9634 \| -8.5921 \| 0.7949 \| 3.6287 \| -342.7202 \| -342.8073 \| -2.4465 \| -2.5246 \|
	\| 0.0092 \| 2.48 \| 4800 \| 0.6804 \| -4.6987 \| -8.2494 \| 0.7832 \| 3.5507 \| -338.5913 \| -339.6177 \| -2.4977 \| -2.5738 \|
	\| 0.0232 \| 2.53 \| 4900 \| 0.6465 \| -4.1657 \| -7.5350 \| 0.7812 \| 3.3694 \| -329.9847 \| -333.1960 \| -2.5170 \| -2.5959 \|
	\| 0.0121 \| 2.58 \| 5000 \| 0.6718 \| -4.7636 \| -8.3913 \| 0.7910 \| 3.6278 \| -340.3017 \| -340.3996 \| -2.5250 \| -2.6042 \|
	\| 0.0104 \| 2.63 \| 5100 \| 0.6863 \| -4.7726 \| -8.4937 \| 0.7930 \| 3.7212 \| -341.5356 \| -340.5081 \| -2.5020 \| -2.5831 \|
	\| 0.0127 \| 2.68 \| 5200 \| 0.7056 \| -5.2268 \| -9.0672 \| 0.7910 \| 3.8404 \| -348.4451 \| -345.9808 \| -2.5054 \| -2.5842 \|
	\| 0.0057 \| 2.74 \| 5300 \| 0.6886 \| -4.8479 \| -8.6269 \| 0.7949 \| 3.7790 \| -343.1393 \| -341.4157 \| -2.5488 \| -2.6248 \|
	\| 0.0132 \| 2.79 \| 5400 \| 0.6839 \| -4.7008 \| -8.4009 \| 0.7930 \| 3.7001 \| -340.4170 \| -339.6432 \| -2.5501 \| -2.6260 \|
	\| 0.0103 \| 2.84 \| 5500 \| 0.6880 \| -4.8373 \| -8.5695 \| 0.7969 \| 3.7322 \| -342.4483 \| -341.2881 \| -2.5405 \| -2.6167 \|
	\| 0.0105 \| 2.89 \| 5600 \| 0.6968 \| -5.0538 \| -8.8490 \| 0.7852 \| 3.7952 \| -345.8162 \| -343.8970 \| -2.5383 \| -2.6136 \|
	\| 0.008 \| 2.94 \| 5700 \| 0.6993 \| -5.0988 \| -8.9206 \| 0.7871 \| 3.8218 \| -346.6779 \| -344.4387 \| -2.5373 \| -2.6125 \|
	\| 0.0047 \| 2.99 \| 5800 \| 0.6975 \| -5.0353 \| -8.8422 \| 0.7949 \| 3.8069 \| -345.7339 \| -343.6734 \| -2.5373 \| -2.6125 \|


	### Framework versions

	- Transformers 4.35.0
	- Pytorch 2.1.0+cu118
	- Datasets 2.14.6
	- Tokenizers 0.14.1

	---
	license: apache-2.0
	base_model: alignment-handbook/zephyr-7b-sft-full
	tags:
	- generated_from_trainer
	model-index:
	- name: zephyr-7b-dpo-full-beta-0.083
	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. -->

	# zephyr-7b-dpo-full-beta-0.083

	This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the None dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.6981
	- Rewards/chosen: -5.0359
	- Rewards/rejected: -8.8405
	- Rewards/accuracies: 0.7930
	- Rewards/margins: 3.8046
	- Logps/rejected: -345.7131
	- Logps/chosen: -343.6803
	- Logits/rejected: -2.5377
	- Logits/chosen: -2.6128

	## 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-07
	- train_batch_size: 8
	- eval_batch_size: 16
	- seed: 42
	- distributed_type: multi-GPU
	- num_devices: 4
	- total_train_batch_size: 32
	- total_eval_batch_size: 64
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- lr_scheduler_warmup_ratio: 0.1
	- num_epochs: 3

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Rewards/chosen \| Rewards/rejected \| Rewards/accuracies \| Rewards/margins \| Logps/rejected \| Logps/chosen \| Logits/rejected \| Logits/chosen \|
	\|:-------------:\|:-----:\|:----:\|:---------------:\|:--------------:\|:----------------:\|:------------------:\|:---------------:\|:--------------:\|:------------:\|:---------------:\|:-------------:\|
	\| 0.6224 \| 0.05 \| 100 \| 0.6037 \| 0.0537 \| -0.1781 \| 0.7129 \| 0.2318 \| -241.3471 \| -282.3603 \| -3.0281 \| -3.0500 \|
	\| 0.4992 \| 0.1 \| 200 \| 0.5157 \| 0.0022 \| -0.7572 \| 0.7520 \| 0.7594 \| -248.3236 \| -282.9802 \| -2.9768 \| -3.0038 \|
	\| 0.5334 \| 0.15 \| 300 \| 0.4983 \| -0.1003 \| -1.0616 \| 0.7695 \| 0.9613 \| -251.9916 \| -284.2161 \| -3.0036 \| -3.0272 \|
	\| 0.5479 \| 0.21 \| 400 \| 0.4918 \| -0.1860 \| -1.2242 \| 0.7656 \| 1.0381 \| -253.9503 \| -285.2488 \| -3.1264 \| -3.1487 \|
	\| 0.531 \| 0.26 \| 500 \| 0.4929 \| -0.4703 \| -1.5754 \| 0.7559 \| 1.1051 \| -258.1821 \| -288.6731 \| -3.0860 \| -3.1247 \|
	\| 0.486 \| 0.31 \| 600 \| 0.5096 \| -0.3559 \| -1.4424 \| 0.7285 \| 1.0865 \| -256.5800 \| -287.2958 \| -3.0519 \| -3.0920 \|
	\| 0.4858 \| 0.36 \| 700 \| 0.5079 \| -0.6230 \| -1.9605 \| 0.7812 \| 1.3375 \| -262.8217 \| -290.5133 \| -2.9452 \| -2.9906 \|
	\| 0.4844 \| 0.41 \| 800 \| 0.4998 \| -0.7197 \| -2.1472 \| 0.7559 \| 1.4275 \| -265.0713 \| -291.6787 \| -2.7574 \| -2.7909 \|
	\| 0.4999 \| 0.46 \| 900 \| 0.4983 \| -0.5951 \| -1.8837 \| 0.7637 \| 1.2886 \| -261.8963 \| -290.1770 \| -2.9454 \| -2.9806 \|
	\| 0.45 \| 0.52 \| 1000 \| 0.4916 \| -0.6703 \| -2.2026 \| 0.7676 \| 1.5323 \| -265.7383 \| -291.0830 \| -2.9158 \| -2.9444 \|
	\| 0.5239 \| 0.57 \| 1100 \| 0.4848 \| -0.8068 \| -2.1600 \| 0.7695 \| 1.3532 \| -265.2255 \| -292.7281 \| -2.8454 \| -2.8788 \|
	\| 0.4766 \| 0.62 \| 1200 \| 0.4974 \| -0.5971 \| -1.8739 \| 0.7441 \| 1.2769 \| -261.7786 \| -290.2007 \| -2.8189 \| -2.8673 \|
	\| 0.497 \| 0.67 \| 1300 \| 0.5048 \| -1.0382 \| -2.4646 \| 0.7266 \| 1.4264 \| -268.8953 \| -295.5161 \| -2.8081 \| -2.8508 \|
	\| 0.5281 \| 0.72 \| 1400 \| 0.5003 \| -1.0137 \| -2.1947 \| 0.7559 \| 1.1810 \| -265.6436 \| -295.2208 \| -2.7945 \| -2.8255 \|
	\| 0.4428 \| 0.77 \| 1500 \| 0.4851 \| -0.8809 \| -2.3005 \| 0.7598 \| 1.4196 \| -266.9182 \| -293.6202 \| -2.7815 \| -2.8139 \|
	\| 0.5192 \| 0.83 \| 1600 \| 0.4758 \| -0.9091 \| -2.3825 \| 0.7539 \| 1.4735 \| -267.9066 \| -293.9598 \| -2.7394 \| -2.7728 \|
	\| 0.533 \| 0.88 \| 1700 \| 0.4753 \| -0.8150 \| -2.1835 \| 0.7676 \| 1.3685 \| -265.5082 \| -292.8266 \| -2.8005 \| -2.8330 \|
	\| 0.5803 \| 0.93 \| 1800 \| 0.4854 \| -0.6814 \| -2.0356 \| 0.75 \| 1.3542 \| -263.7262 \| -291.2166 \| -2.7118 \| -2.7542 \|
	\| 0.4714 \| 0.98 \| 1900 \| 0.4855 \| -0.7688 \| -2.1323 \| 0.7559 \| 1.3634 \| -264.8912 \| -292.2704 \| -2.6864 \| -2.7287 \|
	\| 0.0702 \| 1.03 \| 2000 \| 0.4988 \| -1.4916 \| -3.5339 \| 0.7793 \| 2.0423 \| -281.7779 \| -300.9782 \| -2.6172 \| -2.6670 \|
	\| 0.0732 \| 1.08 \| 2100 \| 0.5188 \| -1.6274 \| -3.8428 \| 0.7793 \| 2.2154 \| -285.4998 \| -302.6147 \| -2.6360 \| -2.6881 \|
	\| 0.077 \| 1.14 \| 2200 \| 0.5274 \| -2.1510 \| -4.2855 \| 0.7812 \| 2.1345 \| -290.8334 \| -308.9228 \| -2.7288 \| -2.7823 \|
	\| 0.0673 \| 1.19 \| 2300 \| 0.5169 \| -1.7308 \| -3.9343 \| 0.7832 \| 2.2035 \| -286.6026 \| -303.8600 \| -2.6971 \| -2.7569 \|
	\| 0.1039 \| 1.24 \| 2400 \| 0.5115 \| -1.7156 \| -3.7812 \| 0.7715 \| 2.0655 \| -284.7573 \| -303.6773 \| -2.6974 \| -2.7420 \|
	\| 0.0961 \| 1.29 \| 2500 \| 0.5290 \| -2.3303 \| -4.5271 \| 0.7734 \| 2.1968 \| -293.7446 \| -311.0832 \| -2.7071 \| -2.7485 \|
	\| 0.1269 \| 1.34 \| 2600 \| 0.5061 \| -1.8237 \| -3.7726 \| 0.7695 \| 1.9490 \| -284.6546 \| -304.9791 \| -2.7066 \| -2.7432 \|
	\| 0.0959 \| 1.39 \| 2700 \| 0.5066 \| -1.8437 \| -3.9127 \| 0.7793 \| 2.0690 \| -286.3417 \| -305.2205 \| -2.7061 \| -2.7584 \|
	\| 0.1009 \| 1.45 \| 2800 \| 0.5241 \| -2.4471 \| -4.6093 \| 0.7852 \| 2.1622 \| -294.7356 \| -312.4907 \| -2.6836 \| -2.7338 \|
	\| 0.0917 \| 1.5 \| 2900 \| 0.5350 \| -2.4581 \| -4.5278 \| 0.75 \| 2.0697 \| -293.7532 \| -312.6228 \| -2.7069 \| -2.7588 \|
	\| 0.0693 \| 1.55 \| 3000 \| 0.5371 \| -2.3570 \| -4.5566 \| 0.7578 \| 2.1996 \| -294.1000 \| -311.4046 \| -2.7179 \| -2.7642 \|
	\| 0.0861 \| 1.6 \| 3100 \| 0.5141 \| -2.1264 \| -4.2158 \| 0.7754 \| 2.0894 \| -289.9940 \| -308.6270 \| -2.7429 \| -2.8104 \|
	\| 0.0851 \| 1.65 \| 3200 \| 0.5175 \| -1.9273 \| -4.0951 \| 0.7695 \| 2.1678 \| -288.5394 \| -306.2276 \| -2.6925 \| -2.7584 \|
	\| 0.0837 \| 1.7 \| 3300 \| 0.5354 \| -2.0696 \| -4.3985 \| 0.7637 \| 2.3289 \| -292.1949 \| -307.9421 \| -2.6726 \| -2.7440 \|
	\| 0.056 \| 1.76 \| 3400 \| 0.5596 \| -2.7840 \| -5.3198 \| 0.7734 \| 2.5358 \| -303.2956 \| -316.5497 \| -2.6498 \| -2.7202 \|
	\| 0.0689 \| 1.81 \| 3500 \| 0.5348 \| -2.3076 \| -4.5718 \| 0.7812 \| 2.2642 \| -294.2832 \| -310.8093 \| -2.7109 \| -2.7732 \|
	\| 0.0934 \| 1.86 \| 3600 \| 0.5539 \| -2.6736 \| -5.0332 \| 0.7734 \| 2.3596 \| -299.8421 \| -315.2191 \| -2.6534 \| -2.7272 \|
	\| 0.0694 \| 1.91 \| 3700 \| 0.5426 \| -2.6655 \| -4.9512 \| 0.7695 \| 2.2857 \| -298.8542 \| -315.1215 \| -2.6730 \| -2.7433 \|
	\| 0.1267 \| 1.96 \| 3800 \| 0.5620 \| -2.8767 \| -5.0299 \| 0.7910 \| 2.1531 \| -299.8019 \| -317.6664 \| -2.6778 \| -2.7430 \|
	\| 0.024 \| 2.01 \| 3900 \| 0.5618 \| -2.9659 \| -5.5768 \| 0.7832 \| 2.6109 \| -306.3921 \| -318.7414 \| -2.6526 \| -2.7240 \|
	\| 0.0171 \| 2.07 \| 4000 \| 0.6117 \| -3.6584 \| -6.6949 \| 0.7793 \| 3.0364 \| -319.8622 \| -327.0849 \| -2.6017 \| -2.6789 \|
	\| 0.0112 \| 2.12 \| 4100 \| 0.6536 \| -3.8851 \| -7.0803 \| 0.7734 \| 3.1953 \| -324.5066 \| -329.8155 \| -2.6007 \| -2.6772 \|
	\| 0.0123 \| 2.17 \| 4200 \| 0.6296 \| -3.5916 \| -6.6239 \| 0.7734 \| 3.0323 \| -319.0072 \| -326.2793 \| -2.6019 \| -2.6741 \|
	\| 0.0135 \| 2.22 \| 4300 \| 0.6245 \| -3.6464 \| -6.7754 \| 0.7832 \| 3.1289 \| -320.8321 \| -326.9404 \| -2.5877 \| -2.6570 \|
	\| 0.0147 \| 2.27 \| 4400 \| 0.6659 \| -4.4576 \| -7.8315 \| 0.7832 \| 3.3739 \| -333.5571 \| -336.7133 \| -2.5400 \| -2.6114 \|
	\| 0.0193 \| 2.32 \| 4500 \| 0.6365 \| -4.0338 \| -7.4212 \| 0.7832 \| 3.3874 \| -328.6134 \| -331.6075 \| -2.4882 \| -2.5622 \|
	\| 0.0141 \| 2.37 \| 4600 \| 0.6966 \| -4.9177 \| -8.5470 \| 0.7930 \| 3.6293 \| -342.1769 \| -342.2570 \| -2.4891 \| -2.5649 \|
	\| 0.0126 \| 2.43 \| 4700 \| 0.6972 \| -4.9634 \| -8.5921 \| 0.7949 \| 3.6287 \| -342.7202 \| -342.8073 \| -2.4465 \| -2.5246 \|
	\| 0.0092 \| 2.48 \| 4800 \| 0.6804 \| -4.6987 \| -8.2494 \| 0.7832 \| 3.5507 \| -338.5913 \| -339.6177 \| -2.4977 \| -2.5738 \|
	\| 0.0232 \| 2.53 \| 4900 \| 0.6465 \| -4.1657 \| -7.5350 \| 0.7812 \| 3.3694 \| -329.9847 \| -333.1960 \| -2.5170 \| -2.5959 \|
	\| 0.0121 \| 2.58 \| 5000 \| 0.6718 \| -4.7636 \| -8.3913 \| 0.7910 \| 3.6278 \| -340.3017 \| -340.3996 \| -2.5250 \| -2.6042 \|
	\| 0.0104 \| 2.63 \| 5100 \| 0.6863 \| -4.7726 \| -8.4937 \| 0.7930 \| 3.7212 \| -341.5356 \| -340.5081 \| -2.5020 \| -2.5831 \|
	\| 0.0127 \| 2.68 \| 5200 \| 0.7056 \| -5.2268 \| -9.0672 \| 0.7910 \| 3.8404 \| -348.4451 \| -345.9808 \| -2.5054 \| -2.5842 \|
	\| 0.0057 \| 2.74 \| 5300 \| 0.6886 \| -4.8479 \| -8.6269 \| 0.7949 \| 3.7790 \| -343.1393 \| -341.4157 \| -2.5488 \| -2.6248 \|
	\| 0.0132 \| 2.79 \| 5400 \| 0.6839 \| -4.7008 \| -8.4009 \| 0.7930 \| 3.7001 \| -340.4170 \| -339.6432 \| -2.5501 \| -2.6260 \|
	\| 0.0103 \| 2.84 \| 5500 \| 0.6880 \| -4.8373 \| -8.5695 \| 0.7969 \| 3.7322 \| -342.4483 \| -341.2881 \| -2.5405 \| -2.6167 \|
	\| 0.0105 \| 2.89 \| 5600 \| 0.6968 \| -5.0538 \| -8.8490 \| 0.7852 \| 3.7952 \| -345.8162 \| -343.8970 \| -2.5383 \| -2.6136 \|
	\| 0.008 \| 2.94 \| 5700 \| 0.6993 \| -5.0988 \| -8.9206 \| 0.7871 \| 3.8218 \| -346.6779 \| -344.4387 \| -2.5373 \| -2.6125 \|
	\| 0.0047 \| 2.99 \| 5800 \| 0.6975 \| -5.0353 \| -8.8422 \| 0.7949 \| 3.8069 \| -345.7339 \| -343.6734 \| -2.5373 \| -2.6125 \|


	### Framework versions

	- Transformers 4.35.0
	- Pytorch 2.1.0+cu118
	- Datasets 2.14.6
	- Tokenizers 0.14.1