--- license: apache-2.0 tags: - generated_from_trainer base_model: bert-large-uncased model-index: - name: pictalk results: [] --- # pictalk This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.3395 ## 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: 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: 50 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 4.4213 | 1.0 | 25 | 3.2802 | | 3.1204 | 2.0 | 50 | 2.8289 | | 2.7337 | 3.0 | 75 | 2.5070 | | 2.4701 | 4.0 | 100 | 2.1833 | | 2.2536 | 5.0 | 125 | 2.0859 | | 2.1284 | 6.0 | 150 | 2.0973 | | 1.9703 | 7.0 | 175 | 1.8079 | | 1.9372 | 8.0 | 200 | 1.8733 | | 1.9115 | 9.0 | 225 | 1.7319 | | 1.7705 | 10.0 | 250 | 1.8154 | | 1.7454 | 11.0 | 275 | 1.6135 | | 1.7338 | 12.0 | 300 | 1.6072 | | 1.6741 | 13.0 | 325 | 1.4479 | | 1.6552 | 14.0 | 350 | 1.6893 | | 1.5546 | 15.0 | 375 | 1.5714 | | 1.5905 | 16.0 | 400 | 1.6661 | | 1.5136 | 17.0 | 425 | 1.6100 | | 1.5403 | 18.0 | 450 | 1.5664 | | 1.4947 | 19.0 | 475 | 1.4803 | | 1.4654 | 20.0 | 500 | 1.6041 | | 1.4449 | 21.0 | 525 | 1.4071 | | 1.4817 | 22.0 | 550 | 1.5543 | | 1.377 | 23.0 | 575 | 1.3897 | | 1.4102 | 24.0 | 600 | 1.4572 | | 1.3246 | 25.0 | 625 | 1.5699 | | 1.3323 | 26.0 | 650 | 1.4316 | | 1.2745 | 27.0 | 675 | 1.5004 | | 1.2589 | 28.0 | 700 | 1.5209 | | 1.3488 | 29.0 | 725 | 1.4734 | | 1.301 | 30.0 | 750 | 1.5197 | | 1.2824 | 31.0 | 775 | 1.5087 | | 1.2771 | 32.0 | 800 | 1.4041 | | 1.2794 | 33.0 | 825 | 1.5773 | | 1.2343 | 34.0 | 850 | 1.3722 | | 1.3235 | 35.0 | 875 | 1.5125 | | 1.2567 | 36.0 | 900 | 1.3877 | | 1.2682 | 37.0 | 925 | 1.5471 | | 1.2028 | 38.0 | 950 | 1.3677 | | 1.2059 | 39.0 | 975 | 1.4233 | | 1.2103 | 40.0 | 1000 | 1.5361 | | 1.1987 | 41.0 | 1025 | 1.5492 | | 1.2853 | 42.0 | 1050 | 1.4274 | | 1.2088 | 43.0 | 1075 | 1.5027 | | 1.2573 | 44.0 | 1100 | 1.5138 | | 1.2511 | 45.0 | 1125 | 1.4198 | | 1.1932 | 46.0 | 1150 | 1.3065 | | 1.1864 | 47.0 | 1175 | 1.4521 | | 1.2362 | 48.0 | 1200 | 1.4576 | | 1.215 | 49.0 | 1225 | 1.4246 | | 1.2118 | 50.0 | 1250 | 1.3395 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.0