metadata
license: apache-2.0
base_model: GanjinZero/biobart-v2-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-2048-inputs-30-epochs
results: []
fine-tuned-2048-inputs-30-epochs
This model is a fine-tuned version of GanjinZero/biobart-v2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8273
- Rouge1: 0.2933
- Rouge2: 0.1173
- Rougel: 0.2662
- Rougelsum: 0.2653
- Gen Len: 15.53
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: 2e-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: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 151 | 0.7529 | 0.2082 | 0.0781 | 0.1878 | 0.1884 | 13.16 |
No log | 2.0 | 302 | 0.7144 | 0.2589 | 0.0817 | 0.2239 | 0.2244 | 13.76 |
No log | 3.0 | 453 | 0.6993 | 0.2409 | 0.0773 | 0.2135 | 0.2136 | 14.52 |
0.7226 | 4.0 | 604 | 0.6957 | 0.2891 | 0.1014 | 0.262 | 0.2618 | 14.27 |
0.7226 | 5.0 | 755 | 0.7037 | 0.2925 | 0.1167 | 0.2656 | 0.267 | 14.73 |
0.7226 | 6.0 | 906 | 0.6971 | 0.2778 | 0.1124 | 0.2511 | 0.2501 | 14.92 |
0.4948 | 7.0 | 1057 | 0.7117 | 0.2816 | 0.1139 | 0.2558 | 0.2553 | 14.93 |
0.4948 | 8.0 | 1208 | 0.7185 | 0.2948 | 0.1192 | 0.2683 | 0.2679 | 14.45 |
0.4948 | 9.0 | 1359 | 0.7250 | 0.3039 | 0.1108 | 0.2748 | 0.2738 | 14.76 |
0.368 | 10.0 | 1510 | 0.7343 | 0.3187 | 0.1267 | 0.2921 | 0.2919 | 14.67 |
0.368 | 11.0 | 1661 | 0.7418 | 0.3067 | 0.1205 | 0.278 | 0.2772 | 15.23 |
0.368 | 12.0 | 1812 | 0.7521 | 0.3023 | 0.1134 | 0.2764 | 0.2756 | 14.91 |
0.368 | 13.0 | 1963 | 0.7556 | 0.2945 | 0.1143 | 0.272 | 0.2713 | 15.01 |
0.2865 | 14.0 | 2114 | 0.7636 | 0.3163 | 0.1246 | 0.2943 | 0.2942 | 15.44 |
0.2865 | 15.0 | 2265 | 0.7722 | 0.2987 | 0.1105 | 0.2705 | 0.2703 | 14.93 |
0.2865 | 16.0 | 2416 | 0.7788 | 0.3047 | 0.1091 | 0.2745 | 0.2744 | 15.29 |
0.2221 | 17.0 | 2567 | 0.7834 | 0.2973 | 0.113 | 0.2698 | 0.269 | 15.11 |
0.2221 | 18.0 | 2718 | 0.7905 | 0.2933 | 0.1139 | 0.2612 | 0.2595 | 15.1 |
0.2221 | 19.0 | 2869 | 0.7945 | 0.2936 | 0.1036 | 0.2637 | 0.2624 | 15.5 |
0.1825 | 20.0 | 3020 | 0.8033 | 0.3167 | 0.1216 | 0.2839 | 0.2837 | 15.54 |
0.1825 | 21.0 | 3171 | 0.8009 | 0.3056 | 0.1139 | 0.2753 | 0.2747 | 15.69 |
0.1825 | 22.0 | 3322 | 0.8085 | 0.2974 | 0.113 | 0.2632 | 0.2621 | 15.37 |
0.1825 | 23.0 | 3473 | 0.8120 | 0.3063 | 0.1191 | 0.2746 | 0.2749 | 15.48 |
0.1498 | 24.0 | 3624 | 0.8163 | 0.3045 | 0.1114 | 0.2736 | 0.2724 | 15.47 |
0.1498 | 25.0 | 3775 | 0.8197 | 0.3091 | 0.1147 | 0.2789 | 0.2788 | 15.51 |
0.1498 | 26.0 | 3926 | 0.8212 | 0.3003 | 0.1211 | 0.2715 | 0.2718 | 15.59 |
0.1329 | 27.0 | 4077 | 0.8230 | 0.3046 | 0.1158 | 0.2751 | 0.275 | 15.5 |
0.1329 | 28.0 | 4228 | 0.8250 | 0.2871 | 0.1118 | 0.2614 | 0.2599 | 15.49 |
0.1329 | 29.0 | 4379 | 0.8275 | 0.303 | 0.1109 | 0.2734 | 0.2737 | 15.57 |
0.1226 | 30.0 | 4530 | 0.8273 | 0.2933 | 0.1173 | 0.2662 | 0.2653 | 15.53 |
Framework versions
- Transformers 4.36.2
- Pytorch 1.12.1+cu113
- Datasets 2.15.0
- Tokenizers 0.15.0