metadata
tags:
- simplification
- generated_from_trainer
metrics:
- rouge
model-index:
- name: NASES-clara-med
results: []
NASES-clara-med
This model is a fine-tuned version of ELiRF/NASES on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.3274
- Rouge1: 43.5242
- Rouge2: 25.5006
- Rougel: 37.6746
- Rougelsum: 37.9494
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: 5.6e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 190 | 2.2062 | 42.852 | 24.8838 | 37.1452 | 37.3371 |
| No log | 2.0 | 380 | 2.3578 | 37.9691 | 19.9011 | 32.0423 | 32.1643 |
| 1.9348 | 3.0 | 570 | 2.3038 | 41.0743 | 22.9938 | 35.4133 | 35.7045 |
| 1.9348 | 4.0 | 760 | 2.2657 | 43.452 | 25.738 | 37.9271 | 38.184 |
| 0.8021 | 5.0 | 950 | 2.3763 | 43.6414 | 25.6831 | 37.8838 | 38.1249 |
| 0.8021 | 6.0 | 1140 | 2.5113 | 43.0882 | 25.4964 | 37.5245 | 37.7459 |
| 0.8021 | 7.0 | 1330 | 2.6203 | 43.164 | 25.1229 | 37.396 | 37.7116 |
| 0.2689 | 8.0 | 1520 | 2.7020 | 43.7588 | 25.7127 | 37.9395 | 38.1406 |
| 0.2689 | 9.0 | 1710 | 2.7533 | 43.3676 | 25.2676 | 37.5607 | 37.8348 |
| 0.1474 | 10.0 | 1900 | 2.8033 | 43.7734 | 25.7325 | 37.8845 | 38.161 |
| 0.1474 | 11.0 | 2090 | 2.8847 | 43.1775 | 25.4384 | 37.4397 | 37.7056 |
| 0.1474 | 12.0 | 2280 | 2.9204 | 43.6149 | 25.6053 | 37.8689 | 38.121 |
| 0.0924 | 13.0 | 2470 | 2.9404 | 43.355 | 25.458 | 37.4775 | 37.7391 |
| 0.0924 | 14.0 | 2660 | 2.9606 | 43.7408 | 25.7361 | 38.0951 | 38.3446 |
| 0.0666 | 15.0 | 2850 | 2.9954 | 43.4987 | 25.5428 | 37.5166 | 37.7468 |
| 0.0666 | 16.0 | 3040 | 3.0491 | 43.8303 | 25.4726 | 37.8056 | 38.0368 |
| 0.0666 | 17.0 | 3230 | 3.0872 | 43.8177 | 25.9315 | 37.9765 | 38.2842 |
| 0.0485 | 18.0 | 3420 | 3.0743 | 43.0783 | 25.1678 | 37.3844 | 37.6768 |
| 0.0485 | 19.0 | 3610 | 3.1571 | 43.5241 | 25.5695 | 37.7233 | 37.9743 |
| 0.0328 | 20.0 | 3800 | 3.1866 | 43.8114 | 25.6402 | 37.7608 | 37.9713 |
| 0.0328 | 21.0 | 3990 | 3.1502 | 43.7322 | 25.6384 | 37.9642 | 38.1954 |
| 0.0328 | 22.0 | 4180 | 3.1723 | 43.5597 | 25.291 | 37.5834 | 37.8289 |
| 0.0264 | 23.0 | 4370 | 3.2214 | 43.251 | 24.8926 | 37.0472 | 37.2819 |
| 0.0264 | 24.0 | 4560 | 3.2764 | 43.469 | 25.2663 | 37.3452 | 37.5562 |
| 0.0169 | 25.0 | 4750 | 3.3104 | 44.0058 | 25.8218 | 38.0374 | 38.2664 |
| 0.0169 | 26.0 | 4940 | 3.2820 | 43.4012 | 25.3515 | 37.5514 | 37.7375 |
| 0.0169 | 27.0 | 5130 | 3.3169 | 43.3498 | 25.2935 | 37.3567 | 37.5987 |
| 0.013 | 28.0 | 5320 | 3.3005 | 43.8029 | 25.6506 | 38.053 | 38.2852 |
| 0.013 | 29.0 | 5510 | 3.3266 | 43.711 | 25.5171 | 37.6826 | 37.9781 |
| 0.0109 | 30.0 | 5700 | 3.3274 | 43.5242 | 25.5006 | 37.6746 | 37.9494 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0
- Datasets 2.8.0
- Tokenizers 0.12.1