--- license: apache-2.0 base_model: google/t5-v1_1-large tags: - generated_from_trainer model-index: - name: Sentiment-google-t5-v1_1-large-inter_model-frequency-human_annots_str results: [] --- # Sentiment-google-t5-v1_1-large-inter_model-frequency-human_annots_str This model is a fine-tuned version of [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.2676 ## 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: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 200 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 20.8675 | 1.0 | 44 | 24.9691 | | 18.2491 | 2.0 | 88 | 16.9536 | | 13.3557 | 3.0 | 132 | 11.4063 | | 11.0809 | 4.0 | 176 | 10.9529 | | 10.1527 | 5.0 | 220 | 10.7258 | | 9.9235 | 6.0 | 264 | 10.5299 | | 9.8499 | 7.0 | 308 | 10.3942 | | 9.5638 | 8.0 | 352 | 10.0279 | | 9.0218 | 9.0 | 396 | 9.4463 | | 8.5704 | 10.0 | 440 | 9.0452 | | 8.3982 | 11.0 | 484 | 8.8619 | | 8.3396 | 12.0 | 528 | 8.7363 | | 7.0951 | 13.0 | 572 | 1.3757 | | 1.1349 | 14.0 | 616 | 1.0516 | | 1.0735 | 15.0 | 660 | 1.0456 | | 1.0787 | 16.0 | 704 | 1.0342 | | 1.0796 | 17.0 | 748 | 1.0342 | | 1.0476 | 18.0 | 792 | 1.0318 | | 1.0566 | 19.0 | 836 | 1.0311 | | 1.0472 | 20.0 | 880 | 1.0247 | | 1.0401 | 21.0 | 924 | 1.0201 | | 1.0725 | 22.0 | 968 | 1.0159 | | 1.0447 | 23.0 | 1012 | 1.0180 | | 1.0477 | 24.0 | 1056 | 1.0121 | | 1.0357 | 25.0 | 1100 | 1.0109 | | 1.0333 | 26.0 | 1144 | 1.0096 | | 1.0282 | 27.0 | 1188 | 1.0078 | | 1.0206 | 28.0 | 1232 | 1.0100 | | 1.0241 | 29.0 | 1276 | 1.0081 | | 1.023 | 30.0 | 1320 | 1.0053 | | 0.9993 | 31.0 | 1364 | 1.0073 | | 1.0104 | 32.0 | 1408 | 1.0079 | | 1.0176 | 33.0 | 1452 | 1.0014 | | 1.0157 | 34.0 | 1496 | 0.9977 | | 1.0204 | 35.0 | 1540 | 0.9960 | | 1.0174 | 36.0 | 1584 | 0.9967 | | 1.0252 | 37.0 | 1628 | 0.9949 | | 1.0076 | 38.0 | 1672 | 0.9913 | | 1.0137 | 39.0 | 1716 | 0.9874 | | 1.0151 | 40.0 | 1760 | 0.9856 | | 0.9907 | 41.0 | 1804 | 0.9843 | | 1.0147 | 42.0 | 1848 | 0.9803 | | 1.001 | 43.0 | 1892 | 0.9777 | | 1.0009 | 44.0 | 1936 | 0.9735 | | 0.9881 | 45.0 | 1980 | 0.9731 | | 0.9973 | 46.0 | 2024 | 0.9761 | | 0.9982 | 47.0 | 2068 | 0.9888 | | 0.9826 | 48.0 | 2112 | 1.0006 | | 0.9739 | 49.0 | 2156 | 0.9766 | | 0.9659 | 50.0 | 2200 | 0.9525 | | 0.9534 | 51.0 | 2244 | 0.9400 | | 0.959 | 52.0 | 2288 | 0.9553 | | 0.9492 | 53.0 | 2332 | 0.9308 | | 0.9629 | 54.0 | 2376 | 0.9325 | | 0.9532 | 55.0 | 2420 | 0.9288 | | 0.9586 | 56.0 | 2464 | 0.9233 | | 0.9511 | 57.0 | 2508 | 0.9228 | | 0.9456 | 58.0 | 2552 | 0.9178 | | 0.937 | 59.0 | 2596 | 0.9140 | | 0.9415 | 60.0 | 2640 | 0.9332 | | 0.9364 | 61.0 | 2684 | 0.9073 | | 0.9304 | 62.0 | 2728 | 0.9112 | | 0.9418 | 63.0 | 2772 | 0.9073 | | 0.9423 | 64.0 | 2816 | 0.9079 | | 0.9277 | 65.0 | 2860 | 0.9062 | | 0.9274 | 66.0 | 2904 | 0.8999 | | 0.9266 | 67.0 | 2948 | 0.8971 | | 0.9231 | 68.0 | 2992 | 0.9003 | | 0.9174 | 69.0 | 3036 | 0.8994 | | 0.9036 | 70.0 | 3080 | 0.8986 | | 0.9112 | 71.0 | 3124 | 0.8925 | | 0.8929 | 72.0 | 3168 | 0.8866 | | 0.9069 | 73.0 | 3212 | 0.8840 | | 0.8922 | 74.0 | 3256 | 0.8818 | | 0.9079 | 75.0 | 3300 | 0.8821 | | 0.8941 | 76.0 | 3344 | 0.8780 | | 0.8952 | 77.0 | 3388 | 0.8824 | | 0.8881 | 78.0 | 3432 | 0.8724 | | 0.884 | 79.0 | 3476 | 0.8684 | | 0.8761 | 80.0 | 3520 | 0.8715 | | 0.8952 | 81.0 | 3564 | 0.8706 | | 0.8871 | 82.0 | 3608 | 0.8654 | | 0.8772 | 83.0 | 3652 | 0.8583 | | 0.8745 | 84.0 | 3696 | 0.8570 | | 0.8683 | 85.0 | 3740 | 0.8490 | | 0.8698 | 86.0 | 3784 | 0.8500 | | 0.8562 | 87.0 | 3828 | 0.8469 | | 0.8636 | 88.0 | 3872 | 0.8465 | | 0.8669 | 89.0 | 3916 | 0.8359 | | 0.8422 | 90.0 | 3960 | 0.8418 | | 0.8568 | 91.0 | 4004 | 0.8332 | | 0.8628 | 92.0 | 4048 | 0.8338 | | 0.8599 | 93.0 | 4092 | 0.8302 | | 0.8471 | 94.0 | 4136 | 0.8235 | | 0.8432 | 95.0 | 4180 | 0.8202 | | 0.8389 | 96.0 | 4224 | 0.8159 | | 0.8347 | 97.0 | 4268 | 0.8218 | | 0.8353 | 98.0 | 4312 | 0.8141 | | 0.8172 | 99.0 | 4356 | 0.8176 | | 0.8303 | 100.0 | 4400 | 0.8078 | | 0.8317 | 101.0 | 4444 | 0.8077 | | 0.8203 | 102.0 | 4488 | 0.8103 | | 0.8224 | 103.0 | 4532 | 0.8076 | | 0.8174 | 104.0 | 4576 | 0.8023 | | 0.8242 | 105.0 | 4620 | 0.7897 | | 0.809 | 106.0 | 4664 | 0.7935 | | 0.8014 | 107.0 | 4708 | 0.7881 | | 0.817 | 108.0 | 4752 | 0.7815 | | 0.7988 | 109.0 | 4796 | 0.7861 | | 0.8003 | 110.0 | 4840 | 0.7716 | | 0.7991 | 111.0 | 4884 | 0.7836 | | 0.7851 | 112.0 | 4928 | 0.7722 | | 0.7884 | 113.0 | 4972 | 0.7716 | | 0.7831 | 114.0 | 5016 | 0.7643 | | 0.7849 | 115.0 | 5060 | 0.7767 | | 0.7846 | 116.0 | 5104 | 0.7602 | | 0.7887 | 117.0 | 5148 | 0.7511 | | 0.7683 | 118.0 | 5192 | 0.7480 | | 0.7856 | 119.0 | 5236 | 0.7532 | | 0.766 | 120.0 | 5280 | 0.7511 | | 0.7663 | 121.0 | 5324 | 0.7490 | | 0.7456 | 122.0 | 5368 | 0.7460 | | 0.7672 | 123.0 | 5412 | 0.7464 | | 0.7553 | 124.0 | 5456 | 0.7324 | | 0.7543 | 125.0 | 5500 | 0.7296 | | 0.7465 | 126.0 | 5544 | 0.7431 | | 0.7525 | 127.0 | 5588 | 0.7310 | | 0.7438 | 128.0 | 5632 | 0.7333 | | 0.7521 | 129.0 | 5676 | 0.7218 | | 0.7501 | 130.0 | 5720 | 0.7170 | | 0.7485 | 131.0 | 5764 | 0.7214 | | 0.7512 | 132.0 | 5808 | 0.7235 | | 0.7554 | 133.0 | 5852 | 0.7140 | | 0.7349 | 134.0 | 5896 | 0.7062 | | 0.7542 | 135.0 | 5940 | 0.7095 | | 0.7303 | 136.0 | 5984 | 0.7111 | | 0.7163 | 137.0 | 6028 | 0.7004 | | 0.7204 | 138.0 | 6072 | 0.7045 | | 0.7091 | 139.0 | 6116 | 0.6918 | | 0.719 | 140.0 | 6160 | 0.6976 | | 0.726 | 141.0 | 6204 | 0.6885 | | 0.7079 | 142.0 | 6248 | 0.6896 | | 0.7043 | 143.0 | 6292 | 0.6966 | | 0.7078 | 144.0 | 6336 | 0.6833 | | 0.711 | 145.0 | 6380 | 0.6839 | | 0.7014 | 146.0 | 6424 | 0.6685 | | 0.7026 | 147.0 | 6468 | 0.6752 | | 0.6927 | 148.0 | 6512 | 0.6802 | | 0.6899 | 149.0 | 6556 | 0.6747 | | 0.7059 | 150.0 | 6600 | 0.6733 | | 0.6855 | 151.0 | 6644 | 0.6551 | | 0.694 | 152.0 | 6688 | 0.6590 | | 0.6896 | 153.0 | 6732 | 0.6568 | | 0.6758 | 154.0 | 6776 | 0.6595 | | 0.7058 | 155.0 | 6820 | 0.6506 | | 0.6761 | 156.0 | 6864 | 0.6586 | | 0.6837 | 157.0 | 6908 | 0.6526 | | 0.6736 | 158.0 | 6952 | 0.6526 | | 0.6738 | 159.0 | 6996 | 0.6434 | | 0.685 | 160.0 | 7040 | 0.6382 | | 0.664 | 161.0 | 7084 | 0.6374 | | 0.6878 | 162.0 | 7128 | 0.6322 | | 0.6552 | 163.0 | 7172 | 0.6338 | | 0.6796 | 164.0 | 7216 | 0.6453 | | 0.6712 | 165.0 | 7260 | 0.6284 | | 0.6683 | 166.0 | 7304 | 0.6249 | | 0.6577 | 167.0 | 7348 | 0.6359 | | 0.6462 | 168.0 | 7392 | 0.6193 | | 0.66 | 169.0 | 7436 | 0.6138 | | 0.6476 | 170.0 | 7480 | 0.6224 | | 0.6444 | 171.0 | 7524 | 0.6195 | | 0.6478 | 172.0 | 7568 | 0.6136 | | 0.6332 | 173.0 | 7612 | 0.5981 | | 0.6456 | 174.0 | 7656 | 0.6004 | | 0.6302 | 175.0 | 7700 | 0.6060 | | 0.6337 | 176.0 | 7744 | 0.6024 | | 0.6282 | 177.0 | 7788 | 0.5936 | | 0.616 | 178.0 | 7832 | 0.5942 | | 0.6324 | 179.0 | 7876 | 0.6038 | | 0.6331 | 180.0 | 7920 | 0.5939 | | 0.627 | 181.0 | 7964 | 0.5881 | | 0.6313 | 182.0 | 8008 | 0.5874 | | 0.626 | 183.0 | 8052 | 0.5868 | | 0.6215 | 184.0 | 8096 | 0.5789 | | 0.6138 | 185.0 | 8140 | 0.5830 | | 0.6235 | 186.0 | 8184 | 0.5900 | | 0.61 | 187.0 | 8228 | 0.5920 | | 0.6218 | 188.0 | 8272 | 0.5830 | | 0.6265 | 189.0 | 8316 | 0.5706 | | 0.6126 | 190.0 | 8360 | 0.5776 | | 0.608 | 191.0 | 8404 | 0.5738 | | 0.6143 | 192.0 | 8448 | 0.5737 | | 0.6065 | 193.0 | 8492 | 0.5714 | | 0.6213 | 194.0 | 8536 | 0.5657 | | 0.6004 | 195.0 | 8580 | 0.5660 | | 0.6229 | 196.0 | 8624 | 0.5646 | | 0.6073 | 197.0 | 8668 | 0.5704 | | 0.6048 | 198.0 | 8712 | 0.5696 | | 0.6008 | 199.0 | 8756 | 0.5619 | | 0.6157 | 200.0 | 8800 | 0.5597 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu121 - Datasets 2.14.5 - Tokenizers 0.14.1