Edit model card

lora-roberta-large-fine-emo

This model is a fine-tuned version of 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
Downloads last month
0
Unable to determine this model’s pipeline type. Check the docs .

Adapter for