File size: 1,900 Bytes
760d17a 5579889 760d17a 5579889 760d17a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: led-base-16384-biolaysum-both-all
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# led-base-16384-biolaysum-both-all
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1320
- Rouge1: 0.4554
- Rouge2: 0.1583
- Rougel: 0.2462
- Rougelsum: 0.2464
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.2477 | 0.69 | 5000 | 2.1940 | 0.4501 | 0.1552 | 0.2441 | 0.2442 |
| 2.0151 | 1.37 | 10000 | 2.1320 | 0.4554 | 0.1583 | 0.2462 | 0.2464 |
| 1.8991 | 2.06 | 15000 | 2.0994 | 0.4561 | 0.1561 | 0.2436 | 0.2437 |
| 1.877 | 2.75 | 20000 | 2.0860 | 0.4588 | 0.1582 | 0.2452 | 0.2453 |
| 1.753 | 3.43 | 25000 | 2.0723 | 0.4566 | 0.1569 | 0.2455 | 0.2457 |
### Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
|