--- license: apache-2.0 base_model: albert-base-v2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: best_model-yelp_polarity-16-13 results: [] --- # best_model-yelp_polarity-16-13 This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3928 - Accuracy: 0.875 ## 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: 1e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 150 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 1 | 0.7228 | 0.5 | | No log | 2.0 | 2 | 0.7227 | 0.5 | | No log | 3.0 | 3 | 0.7227 | 0.5 | | No log | 4.0 | 4 | 0.7225 | 0.5 | | No log | 5.0 | 5 | 0.7224 | 0.5 | | No log | 6.0 | 6 | 0.7221 | 0.5 | | No log | 7.0 | 7 | 0.7219 | 0.5 | | No log | 8.0 | 8 | 0.7216 | 0.5 | | No log | 9.0 | 9 | 0.7213 | 0.5 | | 0.7034 | 10.0 | 10 | 0.7209 | 0.5 | | 0.7034 | 11.0 | 11 | 0.7205 | 0.5 | | 0.7034 | 12.0 | 12 | 0.7200 | 0.5 | | 0.7034 | 13.0 | 13 | 0.7195 | 0.5 | | 0.7034 | 14.0 | 14 | 0.7189 | 0.5 | | 0.7034 | 15.0 | 15 | 0.7183 | 0.5 | | 0.7034 | 16.0 | 16 | 0.7177 | 0.5 | | 0.7034 | 17.0 | 17 | 0.7170 | 0.5 | | 0.7034 | 18.0 | 18 | 0.7163 | 0.5 | | 0.7034 | 19.0 | 19 | 0.7156 | 0.5 | | 0.6925 | 20.0 | 20 | 0.7148 | 0.5 | | 0.6925 | 21.0 | 21 | 0.7140 | 0.5 | | 0.6925 | 22.0 | 22 | 0.7132 | 0.5 | | 0.6925 | 23.0 | 23 | 0.7123 | 0.5 | | 0.6925 | 24.0 | 24 | 0.7113 | 0.5 | | 0.6925 | 25.0 | 25 | 0.7104 | 0.5 | | 0.6925 | 26.0 | 26 | 0.7093 | 0.5 | | 0.6925 | 27.0 | 27 | 0.7082 | 0.5 | | 0.6925 | 28.0 | 28 | 0.7071 | 0.5 | | 0.6925 | 29.0 | 29 | 0.7059 | 0.5 | | 0.6581 | 30.0 | 30 | 0.7047 | 0.5 | | 0.6581 | 31.0 | 31 | 0.7034 | 0.5 | | 0.6581 | 32.0 | 32 | 0.7021 | 0.5 | | 0.6581 | 33.0 | 33 | 0.7007 | 0.5 | | 0.6581 | 34.0 | 34 | 0.6991 | 0.5 | | 0.6581 | 35.0 | 35 | 0.6975 | 0.5 | | 0.6581 | 36.0 | 36 | 0.6958 | 0.5 | | 0.6581 | 37.0 | 37 | 0.6941 | 0.5 | | 0.6581 | 38.0 | 38 | 0.6923 | 0.5 | | 0.6581 | 39.0 | 39 | 0.6904 | 0.5 | | 0.6325 | 40.0 | 40 | 0.6883 | 0.5 | | 0.6325 | 41.0 | 41 | 0.6862 | 0.5 | | 0.6325 | 42.0 | 42 | 0.6841 | 0.5 | | 0.6325 | 43.0 | 43 | 0.6818 | 0.5 | | 0.6325 | 44.0 | 44 | 0.6794 | 0.5 | | 0.6325 | 45.0 | 45 | 0.6770 | 0.5 | | 0.6325 | 46.0 | 46 | 0.6745 | 0.5312 | | 0.6325 | 47.0 | 47 | 0.6718 | 0.5312 | | 0.6325 | 48.0 | 48 | 0.6690 | 0.5312 | | 0.6325 | 49.0 | 49 | 0.6662 | 0.5625 | | 0.573 | 50.0 | 50 | 0.6633 | 0.5625 | | 0.573 | 51.0 | 51 | 0.6602 | 0.5625 | | 0.573 | 52.0 | 52 | 0.6571 | 0.5625 | | 0.573 | 53.0 | 53 | 0.6538 | 0.5625 | | 0.573 | 54.0 | 54 | 0.6504 | 0.5625 | | 0.573 | 55.0 | 55 | 0.6469 | 0.5625 | | 0.573 | 56.0 | 56 | 0.6435 | 0.5625 | | 0.573 | 57.0 | 57 | 0.6401 | 0.625 | | 0.573 | 58.0 | 58 | 0.6368 | 0.625 | | 0.573 | 59.0 | 59 | 0.6336 | 0.6562 | | 0.5136 | 60.0 | 60 | 0.6305 | 0.6875 | | 0.5136 | 61.0 | 61 | 0.6273 | 0.6562 | | 0.5136 | 62.0 | 62 | 0.6240 | 0.6562 | | 0.5136 | 63.0 | 63 | 0.6206 | 0.6562 | | 0.5136 | 64.0 | 64 | 0.6172 | 0.6875 | | 0.5136 | 65.0 | 65 | 0.6138 | 0.6875 | | 0.5136 | 66.0 | 66 | 0.6105 | 0.6875 | | 0.5136 | 67.0 | 67 | 0.6072 | 0.6875 | | 0.5136 | 68.0 | 68 | 0.6038 | 0.6875 | | 0.5136 | 69.0 | 69 | 0.6004 | 0.6875 | | 0.4388 | 70.0 | 70 | 0.5968 | 0.6875 | | 0.4388 | 71.0 | 71 | 0.5931 | 0.7188 | | 0.4388 | 72.0 | 72 | 0.5893 | 0.75 | | 0.4388 | 73.0 | 73 | 0.5854 | 0.75 | | 0.4388 | 74.0 | 74 | 0.5814 | 0.75 | | 0.4388 | 75.0 | 75 | 0.5773 | 0.75 | | 0.4388 | 76.0 | 76 | 0.5732 | 0.75 | | 0.4388 | 77.0 | 77 | 0.5695 | 0.7812 | | 0.4388 | 78.0 | 78 | 0.5660 | 0.7812 | | 0.4388 | 79.0 | 79 | 0.5626 | 0.7812 | | 0.3545 | 80.0 | 80 | 0.5590 | 0.7812 | | 0.3545 | 81.0 | 81 | 0.5553 | 0.7812 | | 0.3545 | 82.0 | 82 | 0.5514 | 0.8125 | | 0.3545 | 83.0 | 83 | 0.5476 | 0.7812 | | 0.3545 | 84.0 | 84 | 0.5437 | 0.7812 | | 0.3545 | 85.0 | 85 | 0.5396 | 0.7812 | | 0.3545 | 86.0 | 86 | 0.5358 | 0.7812 | | 0.3545 | 87.0 | 87 | 0.5316 | 0.7812 | | 0.3545 | 88.0 | 88 | 0.5277 | 0.7812 | | 0.3545 | 89.0 | 89 | 0.5238 | 0.7812 | | 0.2725 | 90.0 | 90 | 0.5197 | 0.7812 | | 0.2725 | 91.0 | 91 | 0.5159 | 0.7812 | | 0.2725 | 92.0 | 92 | 0.5120 | 0.7812 | | 0.2725 | 93.0 | 93 | 0.5079 | 0.7812 | | 0.2725 | 94.0 | 94 | 0.5034 | 0.7812 | | 0.2725 | 95.0 | 95 | 0.4983 | 0.7812 | | 0.2725 | 96.0 | 96 | 0.4934 | 0.7812 | | 0.2725 | 97.0 | 97 | 0.4885 | 0.7812 | | 0.2725 | 98.0 | 98 | 0.4835 | 0.7812 | | 0.2725 | 99.0 | 99 | 0.4790 | 0.8125 | | 0.199 | 100.0 | 100 | 0.4751 | 0.8125 | | 0.199 | 101.0 | 101 | 0.4714 | 0.8125 | | 0.199 | 102.0 | 102 | 0.4677 | 0.8125 | | 0.199 | 103.0 | 103 | 0.4634 | 0.8438 | | 0.199 | 104.0 | 104 | 0.4585 | 0.8438 | | 0.199 | 105.0 | 105 | 0.4532 | 0.875 | | 0.199 | 106.0 | 106 | 0.4484 | 0.875 | | 0.199 | 107.0 | 107 | 0.4439 | 0.875 | | 0.199 | 108.0 | 108 | 0.4400 | 0.875 | | 0.199 | 109.0 | 109 | 0.4363 | 0.875 | | 0.1406 | 110.0 | 110 | 0.4329 | 0.875 | | 0.1406 | 111.0 | 111 | 0.4296 | 0.875 | | 0.1406 | 112.0 | 112 | 0.4259 | 0.875 | | 0.1406 | 113.0 | 113 | 0.4219 | 0.8438 | | 0.1406 | 114.0 | 114 | 0.4176 | 0.8438 | | 0.1406 | 115.0 | 115 | 0.4138 | 0.8438 | | 0.1406 | 116.0 | 116 | 0.4108 | 0.8438 | | 0.1406 | 117.0 | 117 | 0.4077 | 0.8438 | | 0.1406 | 118.0 | 118 | 0.4042 | 0.8438 | | 0.1406 | 119.0 | 119 | 0.4003 | 0.8438 | | 0.0921 | 120.0 | 120 | 0.3968 | 0.8438 | | 0.0921 | 121.0 | 121 | 0.3936 | 0.8438 | | 0.0921 | 122.0 | 122 | 0.3905 | 0.8438 | | 0.0921 | 123.0 | 123 | 0.3878 | 0.8438 | | 0.0921 | 124.0 | 124 | 0.3851 | 0.8438 | | 0.0921 | 125.0 | 125 | 0.3823 | 0.8438 | | 0.0921 | 126.0 | 126 | 0.3802 | 0.8438 | | 0.0921 | 127.0 | 127 | 0.3786 | 0.8438 | | 0.0921 | 128.0 | 128 | 0.3769 | 0.8125 | | 0.0921 | 129.0 | 129 | 0.3748 | 0.8125 | | 0.0543 | 130.0 | 130 | 0.3721 | 0.8125 | | 0.0543 | 131.0 | 131 | 0.3700 | 0.8125 | | 0.0543 | 132.0 | 132 | 0.3685 | 0.8125 | | 0.0543 | 133.0 | 133 | 0.3687 | 0.8125 | | 0.0543 | 134.0 | 134 | 0.3699 | 0.8125 | | 0.0543 | 135.0 | 135 | 0.3711 | 0.8125 | | 0.0543 | 136.0 | 136 | 0.3719 | 0.8125 | | 0.0543 | 137.0 | 137 | 0.3716 | 0.8125 | | 0.0543 | 138.0 | 138 | 0.3706 | 0.8438 | | 0.0543 | 139.0 | 139 | 0.3699 | 0.8438 | | 0.0313 | 140.0 | 140 | 0.3692 | 0.875 | | 0.0313 | 141.0 | 141 | 0.3690 | 0.875 | | 0.0313 | 142.0 | 142 | 0.3690 | 0.875 | | 0.0313 | 143.0 | 143 | 0.3698 | 0.875 | | 0.0313 | 144.0 | 144 | 0.3715 | 0.875 | | 0.0313 | 145.0 | 145 | 0.3737 | 0.875 | | 0.0313 | 146.0 | 146 | 0.3766 | 0.875 | | 0.0313 | 147.0 | 147 | 0.3798 | 0.875 | | 0.0313 | 148.0 | 148 | 0.3838 | 0.875 | | 0.0313 | 149.0 | 149 | 0.3884 | 0.875 | | 0.0183 | 150.0 | 150 | 0.3928 | 0.875 | ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.4.0 - Tokenizers 0.13.3