metadata
base_model: distilbert/distilroberta-base
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: my_model
results: []
my_model
This model is a fine-tuned version of distilbert/distilroberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6879
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.3331 | 1.0 | 781 | 1.6340 |
| 1.6037 | 2.0 | 1562 | 1.4244 |
| 1.4547 | 3.0 | 2343 | 1.2838 |
| 1.3204 | 4.0 | 3124 | 1.2173 |
| 1.271 | 5.0 | 3905 | 1.1427 |
| 1.1674 | 6.0 | 4686 | 1.1616 |
| 1.1311 | 7.0 | 5467 | 1.0644 |
| 1.1 | 8.0 | 6248 | 1.0742 |
| 1.0545 | 9.0 | 7029 | 1.0295 |
| 1.0128 | 10.0 | 7810 | 1.0087 |
| 0.9927 | 11.0 | 8591 | 0.9866 |
| 0.9771 | 12.0 | 9372 | 0.9682 |
| 0.9451 | 13.0 | 10153 | 0.9528 |
| 0.931 | 14.0 | 10934 | 0.9401 |
| 0.9187 | 15.0 | 11715 | 0.9312 |
| 0.881 | 16.0 | 12496 | 0.9076 |
| 0.8569 | 17.0 | 13277 | 0.9218 |
| 0.8394 | 18.0 | 14058 | 0.8740 |
| 0.8279 | 19.0 | 14839 | 0.8659 |
| 0.81 | 20.0 | 15620 | 0.8906 |
| 0.8182 | 21.0 | 16401 | 0.8874 |
| 0.7962 | 22.0 | 17182 | 0.8680 |
| 0.7806 | 23.0 | 17963 | 0.8740 |
| 0.7676 | 24.0 | 18744 | 0.8605 |
| 0.7524 | 25.0 | 19525 | 0.8503 |
| 0.7394 | 26.0 | 20306 | 0.8325 |
| 0.7414 | 27.0 | 21087 | 0.8296 |
| 0.7341 | 28.0 | 21868 | 0.8220 |
| 0.7036 | 29.0 | 22649 | 0.8229 |
| 0.7045 | 30.0 | 23430 | 0.8042 |
| 0.6888 | 31.0 | 24211 | 0.8352 |
| 0.674 | 32.0 | 24992 | 0.8107 |
| 0.6631 | 33.0 | 25773 | 0.8142 |
| 0.6583 | 34.0 | 26554 | 0.8092 |
| 0.645 | 35.0 | 27335 | 0.7717 |
| 0.6463 | 36.0 | 28116 | 0.7887 |
| 0.6418 | 37.0 | 28897 | 0.7757 |
| 0.6197 | 38.0 | 29678 | 0.7712 |
| 0.6154 | 39.0 | 30459 | 0.7823 |
| 0.594 | 40.0 | 31240 | 0.7925 |
| 0.6076 | 41.0 | 32021 | 0.7586 |
| 0.603 | 42.0 | 32802 | 0.7806 |
| 0.5932 | 43.0 | 33583 | 0.7854 |
| 0.5954 | 44.0 | 34364 | 0.7541 |
| 0.5769 | 45.0 | 35145 | 0.7571 |
| 0.5638 | 46.0 | 35926 | 0.7512 |
| 0.5652 | 47.0 | 36707 | 0.7417 |
| 0.5695 | 48.0 | 37488 | 0.7467 |
| 0.5509 | 49.0 | 38269 | 0.7570 |
| 0.5486 | 50.0 | 39050 | 0.7277 |
| 0.5282 | 51.0 | 39831 | 0.7433 |
| 0.54 | 52.0 | 40612 | 0.7541 |
| 0.5335 | 53.0 | 41393 | 0.7425 |
| 0.5247 | 54.0 | 42174 | 0.7474 |
| 0.5207 | 55.0 | 42955 | 0.7470 |
| 0.5101 | 56.0 | 43736 | 0.7217 |
| 0.5159 | 57.0 | 44517 | 0.7333 |
| 0.4914 | 58.0 | 45298 | 0.7235 |
| 0.4821 | 59.0 | 46079 | 0.7203 |
| 0.4825 | 60.0 | 46860 | 0.7358 |
| 0.4819 | 61.0 | 47641 | 0.7401 |
| 0.4826 | 62.0 | 48422 | 0.7297 |
| 0.4748 | 63.0 | 49203 | 0.7295 |
| 0.4796 | 64.0 | 49984 | 0.7360 |
| 0.4727 | 65.0 | 50765 | 0.7122 |
| 0.4615 | 66.0 | 51546 | 0.7306 |
| 0.4552 | 67.0 | 52327 | 0.7031 |
| 0.4515 | 68.0 | 53108 | 0.7274 |
| 0.4512 | 69.0 | 53889 | 0.7035 |
| 0.4447 | 70.0 | 54670 | 0.7401 |
| 0.4391 | 71.0 | 55451 | 0.7341 |
| 0.4369 | 72.0 | 56232 | 0.7117 |
| 0.4401 | 73.0 | 57013 | 0.7115 |
| 0.4299 | 74.0 | 57794 | 0.7003 |
| 0.4198 | 75.0 | 58575 | 0.7175 |
| 0.4256 | 76.0 | 59356 | 0.7062 |
| 0.4052 | 77.0 | 60137 | 0.7269 |
| 0.4238 | 78.0 | 60918 | 0.7084 |
| 0.4141 | 79.0 | 61699 | 0.7111 |
| 0.4084 | 80.0 | 62480 | 0.7058 |
| 0.3943 | 81.0 | 63261 | 0.7057 |
| 0.398 | 82.0 | 64042 | 0.7012 |
| 0.3998 | 83.0 | 64823 | 0.7238 |
| 0.3983 | 84.0 | 65604 | 0.7106 |
| 0.3856 | 85.0 | 66385 | 0.6972 |
| 0.3788 | 86.0 | 67166 | 0.6877 |
| 0.3802 | 87.0 | 67947 | 0.7079 |
| 0.3743 | 88.0 | 68728 | 0.7052 |
| 0.3794 | 89.0 | 69509 | 0.7161 |
| 0.3716 | 90.0 | 70290 | 0.7209 |
| 0.3701 | 91.0 | 71071 | 0.6863 |
| 0.3714 | 92.0 | 71852 | 0.6992 |
| 0.3689 | 93.0 | 72633 | 0.7114 |
| 0.3746 | 94.0 | 73414 | 0.7107 |
| 0.3574 | 95.0 | 74195 | 0.7157 |
| 0.361 | 96.0 | 74976 | 0.7263 |
| 0.3528 | 97.0 | 75757 | 0.7048 |
| 0.3511 | 98.0 | 76538 | 0.6872 |
| 0.3428 | 99.0 | 77319 | 0.7010 |
| 0.3431 | 100.0 | 78100 | 0.7188 |
| 0.3384 | 101.0 | 78881 | 0.7206 |
| 0.3453 | 102.0 | 79662 | 0.6981 |
| 0.3359 | 103.0 | 80443 | 0.7035 |
| 0.3406 | 104.0 | 81224 | 0.7010 |
| 0.3337 | 105.0 | 82005 | 0.7149 |
| 0.3291 | 106.0 | 82786 | 0.6838 |
| 0.3278 | 107.0 | 83567 | 0.6970 |
| 0.3256 | 108.0 | 84348 | 0.6695 |
| 0.3236 | 109.0 | 85129 | 0.6943 |
| 0.3108 | 110.0 | 85910 | 0.7155 |
| 0.3195 | 111.0 | 86691 | 0.6908 |
| 0.3156 | 112.0 | 87472 | 0.7043 |
| 0.3204 | 113.0 | 88253 | 0.7051 |
| 0.3126 | 114.0 | 89034 | 0.6887 |
| 0.3054 | 115.0 | 89815 | 0.6925 |
| 0.3097 | 116.0 | 90596 | 0.6990 |
| 0.3056 | 117.0 | 91377 | 0.7036 |
| 0.2959 | 118.0 | 92158 | 0.7090 |
| 0.3035 | 119.0 | 92939 | 0.6757 |
| 0.3071 | 120.0 | 93720 | 0.6848 |
| 0.2995 | 121.0 | 94501 | 0.6738 |
| 0.2996 | 122.0 | 95282 | 0.6950 |
| 0.293 | 123.0 | 96063 | 0.7070 |
| 0.2914 | 124.0 | 96844 | 0.7104 |
| 0.2901 | 125.0 | 97625 | 0.6719 |
| 0.2954 | 126.0 | 98406 | 0.6926 |
| 0.2922 | 127.0 | 99187 | 0.7024 |
| 0.2839 | 128.0 | 99968 | 0.6878 |
| 0.2894 | 129.0 | 100749 | 0.6826 |
| 0.2868 | 130.0 | 101530 | 0.6851 |
| 0.2784 | 131.0 | 102311 | 0.6863 |
| 0.2848 | 132.0 | 103092 | 0.7175 |
| 0.2659 | 133.0 | 103873 | 0.6802 |
| 0.2732 | 134.0 | 104654 | 0.6903 |
| 0.2718 | 135.0 | 105435 | 0.6900 |
| 0.2741 | 136.0 | 106216 | 0.6928 |
| 0.2802 | 137.0 | 106997 | 0.6824 |
| 0.271 | 138.0 | 107778 | 0.6833 |
| 0.2741 | 139.0 | 108559 | 0.6648 |
| 0.2697 | 140.0 | 109340 | 0.6924 |
| 0.2747 | 141.0 | 110121 | 0.6935 |
| 0.2716 | 142.0 | 110902 | 0.6959 |
| 0.2701 | 143.0 | 111683 | 0.6826 |
| 0.2707 | 144.0 | 112464 | 0.6981 |
| 0.2673 | 145.0 | 113245 | 0.6721 |
| 0.2729 | 146.0 | 114026 | 0.6755 |
| 0.2639 | 147.0 | 114807 | 0.6758 |
| 0.2632 | 148.0 | 115588 | 0.6746 |
| 0.2721 | 149.0 | 116369 | 0.6675 |
| 0.2559 | 150.0 | 117150 | 0.6879 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1