Model save

51dd844 verified 7 months ago

20.4 kB

	---
	license: mit
	library_name: peft
	tags:
	- generated_from_trainer
	base_model: facebook/esm2_t30_150M_UR50D
	metrics:
	- accuracy
	model-index:
	- name: esm2_t130_150M-lora-classifier_2024-04-26_00-25-40
	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. -->

	# esm2_t130_150M-lora-classifier_2024-04-26_00-25-40

	This model is a fine-tuned version of [facebook/esm2_t30_150M_UR50D](https://huggingface.co/facebook/esm2_t30_150M_UR50D) on the None dataset.
	It achieves the following results on the evaluation set:
	- Loss: 1.6470
	- Accuracy: 0.8887

	## 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: 0.0005701568055793089
	- train_batch_size: 28
	- eval_batch_size: 28
	- seed: 8893
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: cosine
	- num_epochs: 300
	- mixed_precision_training: Native AMP

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:--------:\|
	\| 0.7096 \| 1.0 \| 55 \| 0.6718 \| 0.6055 \|
	\| 0.6769 \| 2.0 \| 110 \| 0.6739 \| 0.6055 \|
	\| 0.579 \| 3.0 \| 165 \| 0.6608 \| 0.6484 \|
	\| 0.5726 \| 4.0 \| 220 \| 0.5777 \| 0.7109 \|
	\| 0.6381 \| 5.0 \| 275 \| 0.5020 \| 0.7676 \|
	\| 0.183 \| 6.0 \| 330 \| 0.3725 \| 0.8320 \|
	\| 0.3701 \| 7.0 \| 385 \| 0.3508 \| 0.8535 \|
	\| 0.2147 \| 8.0 \| 440 \| 0.3191 \| 0.8711 \|
	\| 0.1654 \| 9.0 \| 495 \| 0.3036 \| 0.875 \|
	\| 0.1581 \| 10.0 \| 550 \| 0.3761 \| 0.8516 \|
	\| 0.3459 \| 11.0 \| 605 \| 0.3746 \| 0.8594 \|
	\| 0.3325 \| 12.0 \| 660 \| 0.3025 \| 0.8867 \|
	\| 0.1237 \| 13.0 \| 715 \| 0.2983 \| 0.8770 \|
	\| 0.5167 \| 14.0 \| 770 \| 0.3044 \| 0.8887 \|
	\| 0.3541 \| 15.0 \| 825 \| 0.2927 \| 0.8906 \|
	\| 0.0378 \| 16.0 \| 880 \| 0.3669 \| 0.8906 \|
	\| 0.062 \| 17.0 \| 935 \| 0.3298 \| 0.8887 \|
	\| 0.1695 \| 18.0 \| 990 \| 0.2912 \| 0.9004 \|
	\| 0.0444 \| 19.0 \| 1045 \| 0.3034 \| 0.9004 \|
	\| 0.1794 \| 20.0 \| 1100 \| 0.3641 \| 0.8828 \|
	\| 0.0634 \| 21.0 \| 1155 \| 0.3521 \| 0.8867 \|
	\| 0.0446 \| 22.0 \| 1210 \| 0.3438 \| 0.8887 \|
	\| 0.0266 \| 23.0 \| 1265 \| 0.4553 \| 0.8867 \|
	\| 0.2637 \| 24.0 \| 1320 \| 0.4715 \| 0.8867 \|
	\| 0.159 \| 25.0 \| 1375 \| 0.4323 \| 0.8945 \|
	\| 0.2401 \| 26.0 \| 1430 \| 0.6019 \| 0.8809 \|
	\| 0.1317 \| 27.0 \| 1485 \| 0.5549 \| 0.8906 \|
	\| 0.1223 \| 28.0 \| 1540 \| 0.4819 \| 0.8926 \|
	\| 0.0015 \| 29.0 \| 1595 \| 0.6432 \| 0.8711 \|
	\| 0.0007 \| 30.0 \| 1650 \| 0.6480 \| 0.8926 \|
	\| 0.0774 \| 31.0 \| 1705 \| 0.7596 \| 0.8926 \|
	\| 0.1262 \| 32.0 \| 1760 \| 0.7614 \| 0.8809 \|
	\| 0.034 \| 33.0 \| 1815 \| 0.7392 \| 0.8789 \|
	\| 0.0021 \| 34.0 \| 1870 \| 0.9068 \| 0.8848 \|
	\| 0.0003 \| 35.0 \| 1925 \| 0.8724 \| 0.8711 \|
	\| 0.0001 \| 36.0 \| 1980 \| 0.9483 \| 0.8867 \|
	\| 0.0127 \| 37.0 \| 2035 \| 0.9638 \| 0.8828 \|
	\| 0.0001 \| 38.0 \| 2090 \| 0.9105 \| 0.8926 \|
	\| 0.0001 \| 39.0 \| 2145 \| 0.9231 \| 0.8809 \|
	\| 0.0008 \| 40.0 \| 2200 \| 1.0224 \| 0.8867 \|
	\| 0.0001 \| 41.0 \| 2255 \| 1.0666 \| 0.8848 \|
	\| 0.0002 \| 42.0 \| 2310 \| 1.1028 \| 0.8848 \|
	\| 0.0 \| 43.0 \| 2365 \| 0.9653 \| 0.8906 \|
	\| 0.0006 \| 44.0 \| 2420 \| 1.1108 \| 0.8848 \|
	\| 0.0001 \| 45.0 \| 2475 \| 1.2919 \| 0.8730 \|
	\| 0.0002 \| 46.0 \| 2530 \| 1.0834 \| 0.8926 \|
	\| 0.0002 \| 47.0 \| 2585 \| 1.1240 \| 0.8887 \|
	\| 0.0135 \| 48.0 \| 2640 \| 1.1466 \| 0.8887 \|
	\| 0.0008 \| 49.0 \| 2695 \| 1.2674 \| 0.8691 \|
	\| 0.0 \| 50.0 \| 2750 \| 1.1311 \| 0.8887 \|
	\| 0.0086 \| 51.0 \| 2805 \| 1.0957 \| 0.8887 \|
	\| 0.0 \| 52.0 \| 2860 \| 1.1336 \| 0.8789 \|
	\| 0.0007 \| 53.0 \| 2915 \| 1.1494 \| 0.875 \|
	\| 0.0002 \| 54.0 \| 2970 \| 1.0790 \| 0.8848 \|
	\| 0.0002 \| 55.0 \| 3025 \| 1.1489 \| 0.8809 \|
	\| 0.0 \| 56.0 \| 3080 \| 1.1479 \| 0.8867 \|
	\| 0.0022 \| 57.0 \| 3135 \| 1.2092 \| 0.8848 \|
	\| 0.2415 \| 58.0 \| 3190 \| 1.2060 \| 0.8848 \|
	\| 0.7813 \| 59.0 \| 3245 \| 1.3750 \| 0.8613 \|
	\| 0.0 \| 60.0 \| 3300 \| 1.1202 \| 0.875 \|
	\| 0.0 \| 61.0 \| 3355 \| 1.0502 \| 0.8848 \|
	\| 0.0 \| 62.0 \| 3410 \| 1.3270 \| 0.8730 \|
	\| 0.0015 \| 63.0 \| 3465 \| 1.0082 \| 0.875 \|
	\| 0.0002 \| 64.0 \| 3520 \| 0.9724 \| 0.8867 \|
	\| 0.0014 \| 65.0 \| 3575 \| 1.0862 \| 0.8770 \|
	\| 0.0002 \| 66.0 \| 3630 \| 1.1366 \| 0.8730 \|
	\| 0.1868 \| 67.0 \| 3685 \| 1.1838 \| 0.8770 \|
	\| 0.0004 \| 68.0 \| 3740 \| 1.2073 \| 0.875 \|
	\| 0.0007 \| 69.0 \| 3795 \| 1.1793 \| 0.8770 \|
	\| 0.0 \| 70.0 \| 3850 \| 1.2262 \| 0.8652 \|
	\| 0.2838 \| 71.0 \| 3905 \| 1.2415 \| 0.875 \|
	\| 0.0 \| 72.0 \| 3960 \| 1.2346 \| 0.8770 \|
	\| 0.0041 \| 73.0 \| 4015 \| 1.0830 \| 0.8789 \|
	\| 0.0055 \| 74.0 \| 4070 \| 1.0731 \| 0.8867 \|
	\| 0.0 \| 75.0 \| 4125 \| 1.4096 \| 0.8652 \|
	\| 0.0034 \| 76.0 \| 4180 \| 1.1142 \| 0.8711 \|
	\| 0.0 \| 77.0 \| 4235 \| 1.0250 \| 0.8848 \|
	\| 0.0002 \| 78.0 \| 4290 \| 1.0700 \| 0.8691 \|
	\| 0.0009 \| 79.0 \| 4345 \| 0.9032 \| 0.8789 \|
	\| 0.0001 \| 80.0 \| 4400 \| 1.0556 \| 0.8730 \|
	\| 0.0001 \| 81.0 \| 4455 \| 1.0740 \| 0.8770 \|
	\| 0.0002 \| 82.0 \| 4510 \| 1.2571 \| 0.8691 \|
	\| 0.0 \| 83.0 \| 4565 \| 1.2007 \| 0.8809 \|
	\| 0.0 \| 84.0 \| 4620 \| 1.2515 \| 0.875 \|
	\| 0.0001 \| 85.0 \| 4675 \| 1.0750 \| 0.8828 \|
	\| 0.0006 \| 86.0 \| 4730 \| 1.3016 \| 0.8730 \|
	\| 0.0001 \| 87.0 \| 4785 \| 1.2393 \| 0.8809 \|
	\| 0.0 \| 88.0 \| 4840 \| 1.2232 \| 0.8848 \|
	\| 0.0003 \| 89.0 \| 4895 \| 1.2187 \| 0.8789 \|
	\| 0.0 \| 90.0 \| 4950 \| 1.2328 \| 0.8730 \|
	\| 0.0 \| 91.0 \| 5005 \| 1.3026 \| 0.8848 \|
	\| 0.0 \| 92.0 \| 5060 \| 1.3152 \| 0.8770 \|
	\| 0.0 \| 93.0 \| 5115 \| 1.4069 \| 0.875 \|
	\| 0.0 \| 94.0 \| 5170 \| 1.3988 \| 0.8770 \|
	\| 0.0 \| 95.0 \| 5225 \| 1.3675 \| 0.8594 \|
	\| 0.0 \| 96.0 \| 5280 \| 1.3366 \| 0.8770 \|
	\| 0.0003 \| 97.0 \| 5335 \| 1.2140 \| 0.8848 \|
	\| 0.0 \| 98.0 \| 5390 \| 1.3585 \| 0.8711 \|
	\| 0.0 \| 99.0 \| 5445 \| 1.1665 \| 0.8672 \|
	\| 0.0 \| 100.0 \| 5500 \| 1.0947 \| 0.8809 \|
	\| 0.0099 \| 101.0 \| 5555 \| 1.2993 \| 0.8730 \|
	\| 0.0 \| 102.0 \| 5610 \| 1.3578 \| 0.8789 \|
	\| 0.0 \| 103.0 \| 5665 \| 1.3596 \| 0.8867 \|
	\| 0.0006 \| 104.0 \| 5720 \| 1.3164 \| 0.8848 \|
	\| 0.0 \| 105.0 \| 5775 \| 1.4100 \| 0.8770 \|
	\| 0.0 \| 106.0 \| 5830 \| 1.3459 \| 0.875 \|
	\| 0.0005 \| 107.0 \| 5885 \| 1.3783 \| 0.8809 \|
	\| 0.0 \| 108.0 \| 5940 \| 1.2698 \| 0.8770 \|
	\| 0.0 \| 109.0 \| 5995 \| 1.3933 \| 0.8848 \|
	\| 0.0 \| 110.0 \| 6050 \| 1.3813 \| 0.8809 \|
	\| 0.0 \| 111.0 \| 6105 \| 1.5747 \| 0.875 \|
	\| 0.0001 \| 112.0 \| 6160 \| 1.3368 \| 0.8867 \|
	\| 0.0486 \| 113.0 \| 6215 \| 1.3833 \| 0.8828 \|
	\| 0.1476 \| 114.0 \| 6270 \| 1.4943 \| 0.8828 \|
	\| 0.0002 \| 115.0 \| 6325 \| 1.4725 \| 0.8789 \|
	\| 0.0 \| 116.0 \| 6380 \| 1.4614 \| 0.875 \|
	\| 0.0047 \| 117.0 \| 6435 \| 1.6313 \| 0.8770 \|
	\| 0.0 \| 118.0 \| 6490 \| 1.4459 \| 0.8848 \|
	\| 0.0026 \| 119.0 \| 6545 \| 1.4150 \| 0.8730 \|
	\| 0.0 \| 120.0 \| 6600 \| 1.6055 \| 0.8555 \|
	\| 0.0001 \| 121.0 \| 6655 \| 1.3710 \| 0.8789 \|
	\| 0.3319 \| 122.0 \| 6710 \| 1.3940 \| 0.8867 \|
	\| 0.0001 \| 123.0 \| 6765 \| 1.2486 \| 0.875 \|
	\| 0.0002 \| 124.0 \| 6820 \| 1.2946 \| 0.8711 \|
	\| 0.0 \| 125.0 \| 6875 \| 1.2341 \| 0.8711 \|
	\| 0.0 \| 126.0 \| 6930 \| 1.1418 \| 0.8887 \|
	\| 0.0 \| 127.0 \| 6985 \| 1.0713 \| 0.8926 \|
	\| 0.0001 \| 128.0 \| 7040 \| 1.1391 \| 0.8613 \|
	\| 0.1624 \| 129.0 \| 7095 \| 1.2195 \| 0.8789 \|
	\| 0.0 \| 130.0 \| 7150 \| 1.1576 \| 0.8770 \|
	\| 0.0001 \| 131.0 \| 7205 \| 1.2939 \| 0.8730 \|
	\| 0.0 \| 132.0 \| 7260 \| 1.1568 \| 0.8867 \|
	\| 0.0 \| 133.0 \| 7315 \| 1.2117 \| 0.8848 \|
	\| 0.0 \| 134.0 \| 7370 \| 1.1264 \| 0.8926 \|
	\| 0.0 \| 135.0 \| 7425 \| 1.1675 \| 0.8848 \|
	\| 0.0 \| 136.0 \| 7480 \| 1.1983 \| 0.8828 \|
	\| 0.0 \| 137.0 \| 7535 \| 1.2666 \| 0.8770 \|
	\| 0.0001 \| 138.0 \| 7590 \| 1.1287 \| 0.8848 \|
	\| 0.0 \| 139.0 \| 7645 \| 1.0505 \| 0.8848 \|
	\| 0.0 \| 140.0 \| 7700 \| 1.1770 \| 0.8770 \|
	\| 0.0 \| 141.0 \| 7755 \| 1.1749 \| 0.8906 \|
	\| 0.0 \| 142.0 \| 7810 \| 1.1311 \| 0.8711 \|
	\| 0.0 \| 143.0 \| 7865 \| 1.1114 \| 0.8652 \|
	\| 0.0 \| 144.0 \| 7920 \| 1.1419 \| 0.8691 \|
	\| 0.0 \| 145.0 \| 7975 \| 1.1666 \| 0.8691 \|
	\| 0.0 \| 146.0 \| 8030 \| 1.1712 \| 0.8711 \|
	\| 0.0 \| 147.0 \| 8085 \| 1.1831 \| 0.8711 \|
	\| 0.0 \| 148.0 \| 8140 \| 1.1799 \| 0.8711 \|
	\| 0.0 \| 149.0 \| 8195 \| 1.1876 \| 0.8711 \|
	\| 0.0 \| 150.0 \| 8250 \| 1.1884 \| 0.8730 \|
	\| 0.0 \| 151.0 \| 8305 \| 1.2389 \| 0.8730 \|
	\| 0.0 \| 152.0 \| 8360 \| 1.3622 \| 0.875 \|
	\| 0.0 \| 153.0 \| 8415 \| 1.2604 \| 0.8789 \|
	\| 0.0 \| 154.0 \| 8470 \| 1.3336 \| 0.875 \|
	\| 0.0 \| 155.0 \| 8525 \| 1.3496 \| 0.8809 \|
	\| 0.0 \| 156.0 \| 8580 \| 1.3882 \| 0.8555 \|
	\| 0.1815 \| 157.0 \| 8635 \| 1.3679 \| 0.8789 \|
	\| 0.288 \| 158.0 \| 8690 \| 1.3804 \| 0.8691 \|
	\| 0.0 \| 159.0 \| 8745 \| 1.2980 \| 0.8770 \|
	\| 0.0 \| 160.0 \| 8800 \| 1.4075 \| 0.8789 \|
	\| 0.0 \| 161.0 \| 8855 \| 1.4231 \| 0.8789 \|
	\| 0.0 \| 162.0 \| 8910 \| 1.4730 \| 0.875 \|
	\| 0.0019 \| 163.0 \| 8965 \| 1.5861 \| 0.8672 \|
	\| 0.0 \| 164.0 \| 9020 \| 1.4080 \| 0.8809 \|
	\| 0.0005 \| 165.0 \| 9075 \| 1.5852 \| 0.8711 \|
	\| 0.0 \| 166.0 \| 9130 \| 1.5370 \| 0.875 \|
	\| 0.0 \| 167.0 \| 9185 \| 1.5288 \| 0.875 \|
	\| 0.0 \| 168.0 \| 9240 \| 1.5516 \| 0.8711 \|
	\| 0.0 \| 169.0 \| 9295 \| 1.5268 \| 0.8730 \|
	\| 0.0 \| 170.0 \| 9350 \| 1.5061 \| 0.8672 \|
	\| 0.0 \| 171.0 \| 9405 \| 1.4843 \| 0.875 \|
	\| 0.0 \| 172.0 \| 9460 \| 1.5478 \| 0.8633 \|
	\| 0.0 \| 173.0 \| 9515 \| 1.4753 \| 0.8730 \|
	\| 0.0 \| 174.0 \| 9570 \| 1.6709 \| 0.8730 \|
	\| 0.0 \| 175.0 \| 9625 \| 1.6663 \| 0.875 \|
	\| 0.0 \| 176.0 \| 9680 \| 1.6980 \| 0.8672 \|
	\| 0.0 \| 177.0 \| 9735 \| 1.5563 \| 0.8770 \|
	\| 0.0 \| 178.0 \| 9790 \| 1.6146 \| 0.875 \|
	\| 0.0 \| 179.0 \| 9845 \| 1.5599 \| 0.8770 \|
	\| 0.0 \| 180.0 \| 9900 \| 1.5558 \| 0.8789 \|
	\| 0.0 \| 181.0 \| 9955 \| 1.8485 \| 0.8633 \|
	\| 0.0 \| 182.0 \| 10010 \| 1.7223 \| 0.8789 \|
	\| 0.0 \| 183.0 \| 10065 \| 1.7169 \| 0.875 \|
	\| 0.0 \| 184.0 \| 10120 \| 1.7125 \| 0.8711 \|
	\| 0.0 \| 185.0 \| 10175 \| 1.7065 \| 0.8711 \|
	\| 0.0 \| 186.0 \| 10230 \| 1.7748 \| 0.8730 \|
	\| 0.0 \| 187.0 \| 10285 \| 1.6861 \| 0.8789 \|
	\| 0.0 \| 188.0 \| 10340 \| 1.7325 \| 0.8887 \|
	\| 0.0 \| 189.0 \| 10395 \| 1.7658 \| 0.8828 \|
	\| 0.0 \| 190.0 \| 10450 \| 1.7649 \| 0.8809 \|
	\| 0.0 \| 191.0 \| 10505 \| 1.7555 \| 0.8828 \|
	\| 0.0162 \| 192.0 \| 10560 \| 1.8313 \| 0.8691 \|
	\| 0.0001 \| 193.0 \| 10615 \| 1.8314 \| 0.8574 \|
	\| 0.0 \| 194.0 \| 10670 \| 1.7706 \| 0.8672 \|
	\| 0.0 \| 195.0 \| 10725 \| 1.6568 \| 0.8730 \|
	\| 0.0 \| 196.0 \| 10780 \| 1.6568 \| 0.8770 \|
	\| 0.0 \| 197.0 \| 10835 \| 1.6185 \| 0.8848 \|
	\| 0.0 \| 198.0 \| 10890 \| 1.6133 \| 0.8848 \|
	\| 0.0 \| 199.0 \| 10945 \| 1.6129 \| 0.8848 \|
	\| 0.0 \| 200.0 \| 11000 \| 1.6121 \| 0.8848 \|
	\| 0.0 \| 201.0 \| 11055 \| 1.6104 \| 0.8828 \|
	\| 0.0 \| 202.0 \| 11110 \| 1.6075 \| 0.8828 \|
	\| 0.0 \| 203.0 \| 11165 \| 1.6153 \| 0.8867 \|
	\| 0.0 \| 204.0 \| 11220 \| 1.6339 \| 0.8828 \|
	\| 0.0 \| 205.0 \| 11275 \| 1.6164 \| 0.8867 \|
	\| 0.0 \| 206.0 \| 11330 \| 1.6114 \| 0.8848 \|
	\| 0.0 \| 207.0 \| 11385 \| 1.6122 \| 0.8867 \|
	\| 0.0 \| 208.0 \| 11440 \| 1.6079 \| 0.8867 \|
	\| 0.0 \| 209.0 \| 11495 \| 1.6132 \| 0.8867 \|
	\| 0.0 \| 210.0 \| 11550 \| 1.6141 \| 0.8867 \|
	\| 0.0 \| 211.0 \| 11605 \| 1.6122 \| 0.8867 \|
	\| 0.0 \| 212.0 \| 11660 \| 1.6070 \| 0.8867 \|
	\| 0.0 \| 213.0 \| 11715 \| 1.6010 \| 0.8867 \|
	\| 0.0 \| 214.0 \| 11770 \| 1.6562 \| 0.8789 \|
	\| 0.0005 \| 215.0 \| 11825 \| 1.6297 \| 0.8887 \|
	\| 0.0 \| 216.0 \| 11880 \| 1.6070 \| 0.8809 \|
	\| 0.0 \| 217.0 \| 11935 \| 1.6750 \| 0.8770 \|
	\| 0.0 \| 218.0 \| 11990 \| 1.6822 \| 0.8730 \|
	\| 0.0 \| 219.0 \| 12045 \| 1.6819 \| 0.8730 \|
	\| 0.0 \| 220.0 \| 12100 \| 1.6846 \| 0.8770 \|
	\| 0.0 \| 221.0 \| 12155 \| 1.6827 \| 0.875 \|
	\| 0.0 \| 222.0 \| 12210 \| 1.6822 \| 0.875 \|
	\| 0.0 \| 223.0 \| 12265 \| 1.6780 \| 0.8770 \|
	\| 0.0 \| 224.0 \| 12320 \| 1.6813 \| 0.8770 \|
	\| 0.0 \| 225.0 \| 12375 \| 1.6770 \| 0.8770 \|
	\| 0.0 \| 226.0 \| 12430 \| 1.6878 \| 0.8789 \|
	\| 0.0 \| 227.0 \| 12485 \| 1.8890 \| 0.8672 \|
	\| 0.0 \| 228.0 \| 12540 \| 1.6978 \| 0.8828 \|
	\| 0.0 \| 229.0 \| 12595 \| 1.6945 \| 0.8867 \|
	\| 0.0 \| 230.0 \| 12650 \| 1.6960 \| 0.8848 \|
	\| 0.0 \| 231.0 \| 12705 \| 1.6972 \| 0.8867 \|
	\| 0.0 \| 232.0 \| 12760 \| 1.6929 \| 0.8867 \|
	\| 0.0 \| 233.0 \| 12815 \| 1.6911 \| 0.8848 \|
	\| 0.0 \| 234.0 \| 12870 \| 1.6887 \| 0.8867 \|
	\| 0.0 \| 235.0 \| 12925 \| 1.6999 \| 0.8848 \|
	\| 0.0 \| 236.0 \| 12980 \| 1.7000 \| 0.8848 \|
	\| 0.0 \| 237.0 \| 13035 \| 1.6877 \| 0.8867 \|
	\| 0.0 \| 238.0 \| 13090 \| 1.6858 \| 0.8867 \|
	\| 0.0 \| 239.0 \| 13145 \| 1.6859 \| 0.8867 \|
	\| 0.0 \| 240.0 \| 13200 \| 1.6842 \| 0.8867 \|
	\| 0.0 \| 241.0 \| 13255 \| 1.6829 \| 0.8867 \|
	\| 0.0 \| 242.0 \| 13310 \| 1.6800 \| 0.8867 \|
	\| 0.0 \| 243.0 \| 13365 \| 1.6870 \| 0.8848 \|
	\| 0.0 \| 244.0 \| 13420 \| 1.6856 \| 0.8848 \|
	\| 0.0 \| 245.0 \| 13475 \| 1.6831 \| 0.8848 \|
	\| 0.0 \| 246.0 \| 13530 \| 1.6864 \| 0.8828 \|
	\| 0.0 \| 247.0 \| 13585 \| 1.6896 \| 0.8828 \|
	\| 0.0 \| 248.0 \| 13640 \| 1.6900 \| 0.8828 \|
	\| 0.0 \| 249.0 \| 13695 \| 1.6906 \| 0.8848 \|
	\| 0.0 \| 250.0 \| 13750 \| 1.6928 \| 0.8828 \|
	\| 0.0 \| 251.0 \| 13805 \| 1.6943 \| 0.8828 \|
	\| 0.0 \| 252.0 \| 13860 \| 1.6902 \| 0.8789 \|
	\| 0.0 \| 253.0 \| 13915 \| 1.6638 \| 0.8887 \|
	\| 0.0 \| 254.0 \| 13970 \| 1.6632 \| 0.8867 \|
	\| 0.0 \| 255.0 \| 14025 \| 1.6627 \| 0.8867 \|
	\| 0.0 \| 256.0 \| 14080 \| 1.6631 \| 0.8867 \|
	\| 0.0 \| 257.0 \| 14135 \| 1.6626 \| 0.8867 \|
	\| 0.0 \| 258.0 \| 14190 \| 1.6629 \| 0.8867 \|
	\| 0.0 \| 259.0 \| 14245 \| 1.6617 \| 0.8867 \|
	\| 0.0 \| 260.0 \| 14300 \| 1.6606 \| 0.8867 \|
	\| 0.0 \| 261.0 \| 14355 \| 1.6598 \| 0.8867 \|
	\| 0.0 \| 262.0 \| 14410 \| 1.6559 \| 0.8867 \|
	\| 0.0 \| 263.0 \| 14465 \| 1.6564 \| 0.8867 \|
	\| 0.0 \| 264.0 \| 14520 \| 1.6555 \| 0.8867 \|
	\| 0.0 \| 265.0 \| 14575 \| 1.6588 \| 0.8867 \|
	\| 0.0 \| 266.0 \| 14630 \| 1.6565 \| 0.8867 \|
	\| 0.0 \| 267.0 \| 14685 \| 1.6558 \| 0.8867 \|
	\| 0.0 \| 268.0 \| 14740 \| 1.6564 \| 0.8848 \|
	\| 0.0 \| 269.0 \| 14795 \| 1.6578 \| 0.8848 \|
	\| 0.0 \| 270.0 \| 14850 \| 1.6566 \| 0.8848 \|
	\| 0.0 \| 271.0 \| 14905 \| 1.6560 \| 0.8867 \|
	\| 0.0 \| 272.0 \| 14960 \| 1.6587 \| 0.8848 \|
	\| 0.0 \| 273.0 \| 15015 \| 1.6575 \| 0.8867 \|
	\| 0.0 \| 274.0 \| 15070 \| 1.6575 \| 0.8848 \|
	\| 0.0 \| 275.0 \| 15125 \| 1.6570 \| 0.8867 \|
	\| 0.0 \| 276.0 \| 15180 \| 1.6586 \| 0.8848 \|
	\| 0.0 \| 277.0 \| 15235 \| 1.6572 \| 0.8887 \|
	\| 0.0 \| 278.0 \| 15290 \| 1.6577 \| 0.8848 \|
	\| 0.0 \| 279.0 \| 15345 \| 1.6570 \| 0.8867 \|
	\| 0.0 \| 280.0 \| 15400 \| 1.6567 \| 0.8887 \|
	\| 0.0 \| 281.0 \| 15455 \| 1.6548 \| 0.8887 \|
	\| 0.0 \| 282.0 \| 15510 \| 1.6558 \| 0.8867 \|
	\| 0.0 \| 283.0 \| 15565 \| 1.6505 \| 0.8887 \|
	\| 0.0 \| 284.0 \| 15620 \| 1.6515 \| 0.8887 \|
	\| 0.0 \| 285.0 \| 15675 \| 1.6513 \| 0.8887 \|
	\| 0.0 \| 286.0 \| 15730 \| 1.6456 \| 0.8887 \|
	\| 0.0 \| 287.0 \| 15785 \| 1.6471 \| 0.8887 \|
	\| 0.0 \| 288.0 \| 15840 \| 1.6451 \| 0.8887 \|
	\| 0.0 \| 289.0 \| 15895 \| 1.6468 \| 0.8887 \|
	\| 0.0 \| 290.0 \| 15950 \| 1.6470 \| 0.8887 \|
	\| 0.0 \| 291.0 \| 16005 \| 1.6448 \| 0.8887 \|
	\| 0.0 \| 292.0 \| 16060 \| 1.6478 \| 0.8887 \|
	\| 0.0 \| 293.0 \| 16115 \| 1.6475 \| 0.8887 \|
	\| 0.0 \| 294.0 \| 16170 \| 1.6471 \| 0.8887 \|
	\| 0.0 \| 295.0 \| 16225 \| 1.6476 \| 0.8887 \|
	\| 0.0 \| 296.0 \| 16280 \| 1.6475 \| 0.8887 \|
	\| 0.0 \| 297.0 \| 16335 \| 1.6460 \| 0.8887 \|
	\| 0.0 \| 298.0 \| 16390 \| 1.6471 \| 0.8887 \|
	\| 0.0 \| 299.0 \| 16445 \| 1.6469 \| 0.8887 \|
	\| 0.0 \| 300.0 \| 16500 \| 1.6470 \| 0.8887 \|


	### Framework versions

	- PEFT 0.10.0
	- Transformers 4.39.3
	- Pytorch 2.2.1
	- Datasets 2.16.1
	- Tokenizers 0.15.2