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	---
	license: mit
	base_model: roberta-large
	tags:
	- generated_from_trainer
	metrics:
	- accuracy
	- recall
	- f1
	model-index:
	- name: lora-roberta-large-fine-emo
	results: []
	library_name: peft
	---

	<!-- 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. -->

	# lora-roberta-large-fine-emo

	This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.7876
	- Accuracy: 0.7175
	- Prec: 0.6298
	- Recall: 0.5922
	- F1: 0.6045
	- B Acc: 0.5922
	- Prec Joy: 0.6497
	- Recall Joy: 0.7540
	- F1 Joy: 0.6980
	- Prec Anger: 0.6146
	- Recall Anger: 0.6435
	- F1 Anger: 0.6287
	- Prec Disgust: 0.4805
	- Recall Disgust: 0.4393
	- F1 Disgust: 0.4590
	- Prec Fear: 0.6954
	- Recall Fear: 0.5953
	- F1 Fear: 0.6415
	- Prec Neutral: 0.8410
	- Recall Neutral: 0.8250
	- F1 Neutral: 0.8329
	- Prec Sadness: 0.6719
	- Recall Sadness: 0.6124
	- F1 Sadness: 0.6408
	- Prec Surprise: 0.5377
	- Recall Surprise: 0.4215
	- F1 Surprise: 0.4726
	- Prec Amusement: 0.7297
	- Recall Amusement: 0.8284
	- F1 Amusement: 0.7759
	- Prec Anxiety: 0.4420
	- Recall Anxiety: 0.4896
	- F1 Anxiety: 0.4646
	- Prec Guilt: 0.7911
	- Recall Guilt: 0.7740
	- F1 Guilt: 0.7824
	- Prec Love: 0.6545
	- Recall Love: 0.5996
	- F1 Love: 0.6259
	- Prec Optimism: 0.7228
	- Recall Optimism: 0.5915
	- F1 Optimism: 0.6506
	- Prec Pessimism: 0.3571
	- Recall Pessimism: 0.125
	- F1 Pessimism: 0.1852

	## 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: 0.0001
	- train_batch_size: 128
	- eval_batch_size: 64
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- lr_scheduler_warmup_ratio: 0.05
	- num_epochs: 20.0

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| Prec \| Recall \| F1 \| B Acc \| Prec Joy \| Recall Joy \| F1 Joy \| Prec Anger \| Recall Anger \| F1 Anger \| Prec Disgust \| Recall Disgust \| F1 Disgust \| Prec Fear \| Recall Fear \| F1 Fear \| Prec Neutral \| Recall Neutral \| F1 Neutral \| Prec Sadness \| Recall Sadness \| F1 Sadness \| Prec Surprise \| Recall Surprise \| F1 Surprise \| Prec Amusement \| Recall Amusement \| F1 Amusement \| Prec Anxiety \| Recall Anxiety \| F1 Anxiety \| Prec Guilt \| Recall Guilt \| F1 Guilt \| Prec Love \| Recall Love \| F1 Love \| Prec Optimism \| Recall Optimism \| F1 Optimism \| Prec Pessimism \| Recall Pessimism \| F1 Pessimism \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:--------:\|:------:\|:------:\|:------:\|:------:\|:--------:\|:----------:\|:------:\|:----------:\|:------------:\|:--------:\|:------------:\|:--------------:\|:----------:\|:---------:\|:-----------:\|:-------:\|:------------:\|:--------------:\|:----------:\|:------------:\|:--------------:\|:----------:\|:-------------:\|:---------------:\|:-----------:\|:--------------:\|:----------------:\|:------------:\|:------------:\|:--------------:\|:----------:\|:----------:\|:------------:\|:--------:\|:---------:\|:-----------:\|:-------:\|:-------------:\|:---------------:\|:-----------:\|:--------------:\|:----------------:\|:------------:\|
	\| 1.0157 \| 1.0 \| 1756 \| 0.9691 \| 0.6663 \| 0.5337 \| 0.5038 \| 0.5122 \| 0.5038 \| 0.6173 \| 0.6805 \| 0.6474 \| 0.5681 \| 0.4796 \| 0.5201 \| 0.4619 \| 0.3893 \| 0.4225 \| 0.6567 \| 0.4117 \| 0.5061 \| 0.8134 \| 0.8269 \| 0.8201 \| 0.5633 \| 0.56 \| 0.5616 \| 0.4613 \| 0.3204 \| 0.3782 \| 0.6554 \| 0.7657 \| 0.7062 \| 0.3637 \| 0.5292 \| 0.4311 \| 0.7048 \| 0.6130 \| 0.6557 \| 0.4626 \| 0.5186 \| 0.4890 \| 0.6092 \| 0.4538 \| 0.5202 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.9186 \| 2.0 \| 3512 \| 0.8979 \| 0.6873 \| 0.5497 \| 0.5388 \| 0.5376 \| 0.5388 \| 0.6239 \| 0.7230 \| 0.6698 \| 0.5644 \| 0.5817 \| 0.5729 \| 0.4373 \| 0.4357 \| 0.4365 \| 0.5923 \| 0.5743 \| 0.5831 \| 0.8235 \| 0.8298 \| 0.8266 \| 0.6103 \| 0.5373 \| 0.5715 \| 0.5451 \| 0.2796 \| 0.3696 \| 0.5699 \| 0.8746 \| 0.6901 \| 0.4437 \| 0.4174 \| 0.4302 \| 0.7510 \| 0.6872 \| 0.7177 \| 0.5687 \| 0.5129 \| 0.5393 \| 0.6165 \| 0.5509 \| 0.5818 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.8686 \| 3.0 \| 5268 \| 0.8550 \| 0.6993 \| 0.5880 \| 0.5603 \| 0.5700 \| 0.5603 \| 0.6758 \| 0.6879 \| 0.6818 \| 0.5462 \| 0.6339 \| 0.5868 \| 0.4386 \| 0.4339 \| 0.4363 \| 0.6578 \| 0.5485 \| 0.5982 \| 0.8159 \| 0.8431 \| 0.8293 \| 0.6360 \| 0.5707 \| 0.6015 \| 0.4874 \| 0.3753 \| 0.4241 \| 0.6702 \| 0.8251 \| 0.7396 \| 0.4647 \| 0.4431 \| 0.4537 \| 0.8147 \| 0.6600 \| 0.7293 \| 0.5840 \| 0.5634 \| 0.5735 \| 0.6426 \| 0.5994 \| 0.6202 \| 0.2105 \| 0.1 \| 0.1356 \|
	\| 0.8386 \| 4.0 \| 7024 \| 0.8276 \| 0.7080 \| 0.6131 \| 0.5607 \| 0.5805 \| 0.5607 \| 0.6812 \| 0.6885 \| 0.6848 \| 0.6102 \| 0.5716 \| 0.5903 \| 0.4691 \| 0.4339 \| 0.4508 \| 0.6514 \| 0.5813 \| 0.6143 \| 0.7868 \| 0.8752 \| 0.8286 \| 0.6617 \| 0.5702 \| 0.6126 \| 0.5489 \| 0.3441 \| 0.4230 \| 0.7143 \| 0.8251 \| 0.7657 \| 0.4824 \| 0.4481 \| 0.4646 \| 0.7817 \| 0.7251 \| 0.7523 \| 0.6292 \| 0.5500 \| 0.5870 \| 0.6866 \| 0.5759 \| 0.6264 \| 0.2667 \| 0.1 \| 0.1455 \|
	\| 0.8125 \| 5.0 \| 8780 \| 0.8200 \| 0.7102 \| 0.6011 \| 0.5845 \| 0.5887 \| 0.5845 \| 0.6745 \| 0.7044 \| 0.6891 \| 0.6341 \| 0.5779 \| 0.6047 \| 0.4914 \| 0.4071 \| 0.4453 \| 0.7038 \| 0.5836 \| 0.6381 \| 0.8196 \| 0.8475 \| 0.8333 \| 0.6499 \| 0.5858 \| 0.6162 \| 0.4950 \| 0.4237 \| 0.4565 \| 0.6650 \| 0.8845 \| 0.7592 \| 0.4218 \| 0.5361 \| 0.4721 \| 0.7771 \| 0.7251 \| 0.7502 \| 0.6509 \| 0.5777 \| 0.6121 \| 0.6140 \| 0.6197 \| 0.6168 \| 0.2174 \| 0.125 \| 0.1587 \|
	\| 0.7981 \| 6.0 \| 10536 \| 0.8111 \| 0.7131 \| 0.5989 \| 0.5719 \| 0.5793 \| 0.5719 \| 0.6839 \| 0.6987 \| 0.6912 \| 0.6277 \| 0.6090 \| 0.6182 \| 0.5151 \| 0.3964 \| 0.4480 \| 0.6894 \| 0.6023 \| 0.6429 \| 0.8023 \| 0.8626 \| 0.8313 \| 0.7311 \| 0.5231 \| 0.6098 \| 0.5577 \| 0.3688 \| 0.4440 \| 0.6710 \| 0.8548 \| 0.7518 \| 0.4138 \| 0.5697 \| 0.4794 \| 0.8109 \| 0.7288 \| 0.7676 \| 0.5881 \| 0.6301 \| 0.6084 \| 0.6943 \| 0.5900 \| 0.6379 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.7883 \| 7.0 \| 12292 \| 0.8049 \| 0.7133 \| 0.6065 \| 0.5998 \| 0.6008 \| 0.5998 \| 0.6620 \| 0.7362 \| 0.6971 \| 0.6193 \| 0.6080 \| 0.6136 \| 0.4283 \| 0.4911 \| 0.4576 \| 0.6456 \| 0.6199 \| 0.6325 \| 0.8404 \| 0.8292 \| 0.8348 \| 0.6721 \| 0.5849 \| 0.6255 \| 0.5047 \| 0.4075 \| 0.4509 \| 0.7096 \| 0.8548 \| 0.7754 \| 0.4352 \| 0.5114 \| 0.4702 \| 0.7722 \| 0.7541 \| 0.7630 \| 0.6345 \| 0.6072 \| 0.6206 \| 0.7111 \| 0.5931 \| 0.6468 \| 0.25 \| 0.2 \| 0.2222 \|
	\| 0.7724 \| 8.0 \| 14048 \| 0.7981 \| 0.7174 \| 0.6296 \| 0.5832 \| 0.5941 \| 0.5832 \| 0.6869 \| 0.7086 \| 0.6976 \| 0.6292 \| 0.6277 \| 0.6284 \| 0.5897 \| 0.3696 \| 0.4544 \| 0.6136 \| 0.6538 \| 0.6331 \| 0.8224 \| 0.8514 \| 0.8367 \| 0.6859 \| 0.5716 \| 0.6235 \| 0.5257 \| 0.4075 \| 0.4591 \| 0.7333 \| 0.7987 \| 0.7646 \| 0.4078 \| 0.5618 \| 0.4725 \| 0.7782 \| 0.7740 \| 0.7761 \| 0.6324 \| 0.6101 \| 0.6211 \| 0.7046 \| 0.5712 \| 0.6309 \| 0.375 \| 0.075 \| 0.1250 \|
	\| 0.7644 \| 9.0 \| 15804 \| 0.7984 \| 0.7155 \| 0.6223 \| 0.5727 \| 0.5888 \| 0.5727 \| 0.6514 \| 0.7481 \| 0.6964 \| 0.6069 \| 0.6473 \| 0.6265 \| 0.5131 \| 0.4196 \| 0.4617 \| 0.6629 \| 0.6234 \| 0.6426 \| 0.8348 \| 0.8311 \| 0.8329 \| 0.6112 \| 0.6533 \| 0.6316 \| 0.5514 \| 0.3806 \| 0.4504 \| 0.7335 \| 0.8086 \| 0.7692 \| 0.4865 \| 0.3749 \| 0.4235 \| 0.8020 \| 0.7396 \| 0.7695 \| 0.6567 \| 0.5891 \| 0.6211 \| 0.7298 \| 0.5790 \| 0.6457 \| 0.25 \| 0.05 \| 0.0833 \|
	\| 0.7531 \| 10.0 \| 17560 \| 0.7929 \| 0.7181 \| 0.6020 \| 0.5761 \| 0.5853 \| 0.5761 \| 0.6524 \| 0.7454 \| 0.6958 \| 0.6170 \| 0.6291 \| 0.6230 \| 0.5325 \| 0.3804 \| 0.4437 \| 0.6675 \| 0.6222 \| 0.6441 \| 0.8269 \| 0.8428 \| 0.8348 \| 0.6892 \| 0.5924 \| 0.6372 \| 0.5144 \| 0.4215 \| 0.4634 \| 0.6939 \| 0.8680 \| 0.7713 \| 0.4655 \| 0.4402 \| 0.4525 \| 0.7802 \| 0.7703 \| 0.7753 \| 0.6405 \| 0.6149 \| 0.6274 \| 0.7464 \| 0.5618 \| 0.6411 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.7462 \| 11.0 \| 19316 \| 0.7868 \| 0.7187 \| 0.6001 \| 0.5776 \| 0.5861 \| 0.5776 \| 0.6634 \| 0.7412 \| 0.7001 \| 0.6197 \| 0.6425 \| 0.6309 \| 0.4802 \| 0.4125 \| 0.4438 \| 0.6403 \| 0.6246 \| 0.6323 \| 0.8266 \| 0.8413 \| 0.8339 \| 0.6714 \| 0.6067 \| 0.6374 \| 0.5649 \| 0.3978 \| 0.4669 \| 0.7096 \| 0.8548 \| 0.7754 \| 0.4643 \| 0.4688 \| 0.4665 \| 0.7973 \| 0.7468 \| 0.7712 \| 0.6703 \| 0.5815 \| 0.6228 \| 0.6930 \| 0.5900 \| 0.6374 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.7357 \| 12.0 \| 21072 \| 0.7876 \| 0.7175 \| 0.6298 \| 0.5922 \| 0.6045 \| 0.5922 \| 0.6497 \| 0.7540 \| 0.6980 \| 0.6146 \| 0.6435 \| 0.6287 \| 0.4805 \| 0.4393 \| 0.4590 \| 0.6954 \| 0.5953 \| 0.6415 \| 0.8410 \| 0.8250 \| 0.8329 \| 0.6719 \| 0.6124 \| 0.6408 \| 0.5377 \| 0.4215 \| 0.4726 \| 0.7297 \| 0.8284 \| 0.7759 \| 0.4420 \| 0.4896 \| 0.4646 \| 0.7911 \| 0.7740 \| 0.7824 \| 0.6545 \| 0.5996 \| 0.6259 \| 0.7228 \| 0.5915 \| 0.6506 \| 0.3571 \| 0.125 \| 0.1852 \|
	\| 0.7242 \| 13.0 \| 22828 \| 0.7810 \| 0.7205 \| 0.6004 \| 0.5846 \| 0.5903 \| 0.5846 \| 0.6679 \| 0.7310 \| 0.6980 \| 0.6422 \| 0.6277 \| 0.6348 \| 0.4782 \| 0.4304 \| 0.4530 \| 0.6712 \| 0.6304 \| 0.6502 \| 0.8237 \| 0.8440 \| 0.8337 \| 0.6598 \| 0.6231 \| 0.6409 \| 0.5565 \| 0.4022 \| 0.4669 \| 0.7213 \| 0.8713 \| 0.7892 \| 0.4847 \| 0.4243 \| 0.4525 \| 0.7698 \| 0.7740 \| 0.7719 \| 0.6276 \| 0.6330 \| 0.6303 \| 0.7022 \| 0.6088 \| 0.6521 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.7216 \| 14.0 \| 24584 \| 0.7839 \| 0.7200 \| 0.6543 \| 0.5946 \| 0.6044 \| 0.5946 \| 0.6680 \| 0.7423 \| 0.7032 \| 0.5927 \| 0.6814 \| 0.6340 \| 0.5271 \| 0.4 \| 0.4548 \| 0.7023 \| 0.6070 \| 0.6512 \| 0.8409 \| 0.8267 \| 0.8337 \| 0.6973 \| 0.5907 \| 0.6396 \| 0.5560 \| 0.4108 \| 0.4725 \| 0.7330 \| 0.8515 \| 0.7878 \| 0.4193 \| 0.5707 \| 0.4835 \| 0.7890 \| 0.7776 \| 0.7832 \| 0.6516 \| 0.6044 \| 0.6271 \| 0.7283 \| 0.5915 \| 0.6528 \| 0.6 \| 0.075 \| 0.1333 \|
	\| 0.7136 \| 15.0 \| 26340 \| 0.7812 \| 0.7228 \| 0.6390 \| 0.5889 \| 0.6012 \| 0.5889 \| 0.6691 \| 0.7383 \| 0.7020 \| 0.6679 \| 0.5898 \| 0.6265 \| 0.5154 \| 0.4482 \| 0.4795 \| 0.6839 \| 0.6175 \| 0.6490 \| 0.8221 \| 0.8489 \| 0.8353 \| 0.6613 \| 0.6213 \| 0.6407 \| 0.5508 \| 0.4140 \| 0.4727 \| 0.7260 \| 0.8482 \| 0.7823 \| 0.4718 \| 0.4718 \| 0.4718 \| 0.7932 \| 0.7631 \| 0.7779 \| 0.6205 \| 0.6454 \| 0.6327 \| 0.7254 \| 0.5994 \| 0.6564 \| 0.4 \| 0.05 \| 0.0889 \|
	\| 0.7092 \| 16.0 \| 28096 \| 0.7793 \| 0.7225 \| 0.6047 \| 0.5858 \| 0.5928 \| 0.5858 \| 0.6690 \| 0.7391 \| 0.7023 \| 0.6432 \| 0.6296 \| 0.6363 \| 0.5098 \| 0.4179 \| 0.4593 \| 0.6622 \| 0.6398 \| 0.6508 \| 0.8315 \| 0.8426 \| 0.8370 \| 0.6647 \| 0.616 \| 0.6394 \| 0.5688 \| 0.4 \| 0.4697 \| 0.7301 \| 0.8482 \| 0.7847 \| 0.4468 \| 0.4896 \| 0.4672 \| 0.7833 \| 0.7649 \| 0.7740 \| 0.6341 \| 0.6177 \| 0.6258 \| 0.7182 \| 0.6103 \| 0.6599 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.7052 \| 17.0 \| 29852 \| 0.7800 \| 0.7224 \| 0.6070 \| 0.5875 \| 0.5949 \| 0.5875 \| 0.6625 \| 0.7469 \| 0.7021 \| 0.6365 \| 0.6344 \| 0.6355 \| 0.5312 \| 0.4107 \| 0.4632 \| 0.6874 \| 0.6199 \| 0.6519 \| 0.8338 \| 0.8367 \| 0.8353 \| 0.6665 \| 0.62 \| 0.6424 \| 0.5529 \| 0.4161 \| 0.4748 \| 0.7270 \| 0.8614 \| 0.7885 \| 0.4559 \| 0.4906 \| 0.4726 \| 0.7996 \| 0.7649 \| 0.7819 \| 0.6444 \| 0.6168 \| 0.6303 \| 0.6935 \| 0.6197 \| 0.6545 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.6988 \| 18.0 \| 31608 \| 0.7770 \| 0.7233 \| 0.6089 \| 0.5873 \| 0.5950 \| 0.5873 \| 0.6674 \| 0.7446 \| 0.7038 \| 0.6192 \| 0.6483 \| 0.6334 \| 0.5072 \| 0.4393 \| 0.4708 \| 0.6937 \| 0.6199 \| 0.6547 \| 0.8287 \| 0.8427 \| 0.8356 \| 0.6801 \| 0.6084 \| 0.6423 \| 0.5853 \| 0.3946 \| 0.4714 \| 0.7216 \| 0.8812 \| 0.7935 \| 0.4646 \| 0.4738 \| 0.4691 \| 0.7885 \| 0.7685 \| 0.7784 \| 0.6457 \| 0.6063 \| 0.6254 \| 0.7132 \| 0.6072 \| 0.6560 \| 0.0 \| 0.0 \| 0.0 \|
	\| 0.7021 \| 19.0 \| 33364 \| 0.7778 \| 0.7238 \| 0.6356 \| 0.5900 \| 0.6000 \| 0.5900 \| 0.6731 \| 0.7389 \| 0.7045 \| 0.6348 \| 0.6306 \| 0.6327 \| 0.5010 \| 0.4482 \| 0.4731 \| 0.6972 \| 0.6222 \| 0.6576 \| 0.8285 \| 0.8431 \| 0.8358 \| 0.6651 \| 0.6249 \| 0.6444 \| 0.5852 \| 0.3989 \| 0.4744 \| 0.7421 \| 0.8548 \| 0.7945 \| 0.4534 \| 0.4817 \| 0.4671 \| 0.7896 \| 0.7667 \| 0.7780 \| 0.6365 \| 0.6311 \| 0.6338 \| 0.7228 \| 0.6041 \| 0.6581 \| 0.3333 \| 0.025 \| 0.0465 \|
	\| 0.703 \| 20.0 \| 35120 \| 0.7772 \| 0.7230 \| 0.6333 \| 0.5894 \| 0.5987 \| 0.5894 \| 0.6716 \| 0.7385 \| 0.7035 \| 0.6341 \| 0.6310 \| 0.6326 \| 0.5083 \| 0.4375 \| 0.4702 \| 0.6816 \| 0.6234 \| 0.6512 \| 0.8272 \| 0.8432 \| 0.8351 \| 0.6761 \| 0.6133 \| 0.6432 \| 0.5690 \| 0.4032 \| 0.4720 \| 0.7358 \| 0.8548 \| 0.7908 \| 0.4536 \| 0.4886 \| 0.4705 \| 0.7860 \| 0.7703 \| 0.7781 \| 0.6407 \| 0.6273 \| 0.6339 \| 0.7153 \| 0.6056 \| 0.6559 \| 0.3333 \| 0.025 \| 0.0465 \|


	### Framework versions

	- Transformers 4.32.0.dev0
	- Pytorch 2.0.1
	- Datasets 2.12.0
	- Tokenizers 0.11.0