--- base_model: google/pegasus-x-base tags: - generated_from_trainer model-index: - name: pegasusx-AMI-text-summarizer results: [] --- # pegasusx-AMI-text-summarizer This model is a fine-tuned version of [google/pegasus-x-base](https://huggingface.co/google/pegasus-x-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.9024 ## 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: 1 - eval_batch_size: 1 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 35 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 4.6836 | 0.77 | 10 | 4.2972 | | 4.6013 | 1.53 | 20 | 4.1099 | | 4.5902 | 2.3 | 30 | 3.9257 | | 4.3479 | 3.06 | 40 | 3.8087 | | 4.1995 | 3.83 | 50 | 3.6779 | | 4.0121 | 4.59 | 60 | 3.5480 | | 3.8925 | 5.36 | 70 | 3.4199 | | 3.7548 | 6.12 | 80 | 3.2936 | | 3.4644 | 6.89 | 90 | 3.1752 | | 3.2484 | 7.66 | 100 | 3.0529 | | 3.2456 | 8.42 | 110 | 2.9345 | | 3.2281 | 9.19 | 120 | 2.8282 | | 2.9944 | 9.95 | 130 | 2.7188 | | 2.8439 | 10.72 | 140 | 2.6208 | | 2.8192 | 11.48 | 150 | 2.5434 | | 2.631 | 12.25 | 160 | 2.4852 | | 2.5715 | 13.01 | 170 | 2.4277 | | 2.5404 | 13.78 | 180 | 2.3876 | | 2.4297 | 14.55 | 190 | 2.3507 | | 2.4243 | 15.31 | 200 | 2.3110 | | 2.4517 | 16.08 | 210 | 2.2733 | | 2.3127 | 16.84 | 220 | 2.2454 | | 2.3058 | 17.61 | 230 | 2.2127 | | 2.1694 | 18.37 | 240 | 2.1808 | | 2.1908 | 19.14 | 250 | 2.1532 | | 2.1474 | 19.9 | 260 | 2.1234 | | 2.1264 | 20.67 | 270 | 2.1139 | | 2.0156 | 21.44 | 280 | 2.0933 | | 2.0264 | 22.2 | 290 | 2.0611 | | 2.0338 | 22.97 | 300 | 2.0448 | | 2.055 | 23.73 | 310 | 2.0302 | | 1.7735 | 24.5 | 320 | 2.0117 | | 1.8999 | 25.26 | 330 | 2.0005 | | 1.8606 | 26.03 | 340 | 1.9795 | | 1.7847 | 26.79 | 350 | 1.9744 | | 1.7478 | 27.56 | 360 | 1.9614 | | 1.8806 | 28.33 | 370 | 1.9514 | | 1.6817 | 29.09 | 380 | 1.9436 | | 1.689 | 29.86 | 390 | 1.9351 | | 1.649 | 30.62 | 400 | 1.9292 | | 1.715 | 31.39 | 410 | 1.9181 | | 1.5847 | 32.15 | 420 | 1.9077 | | 1.6016 | 32.92 | 430 | 1.9112 | | 1.532 | 33.68 | 440 | 1.9018 | | 1.4849 | 34.45 | 450 | 1.9024 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.0 - Tokenizers 0.15.2