File size: 2,316 Bytes
5bf91d0 |
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 69 70 71 72 73 74 75 76 77 78 79 80 |
---
tags:
- generated_from_trainer
datasets:
- pub_med_summarization_dataset
metrics:
- rouge
model-index:
- name: pegasus-cnn_dailymail-finetuned-pubmed
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: pub_med_summarization_dataset
type: pub_med_summarization_dataset
args: document
metrics:
- name: Rouge1
type: rouge
value: 37.2569
---
<!-- 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. -->
# pegasus-cnn_dailymail-finetuned-pubmed
This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the pub_med_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8050
- Rouge1: 37.2569
- Rouge2: 15.8205
- Rougel: 24.1969
- Rougelsum: 34.0331
- Gen Len: 125.892
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.2449 | 1.0 | 1000 | 1.8942 | 36.4494 | 14.9948 | 23.8279 | 33.3081 | 124.482 |
| 2.0803 | 2.0 | 2000 | 1.8440 | 36.998 | 15.4992 | 24.091 | 33.6614 | 125.678 |
| 2.0166 | 3.0 | 3000 | 1.8176 | 37.4703 | 16.0358 | 24.5735 | 34.1789 | 125.094 |
| 1.9911 | 4.0 | 4000 | 1.8055 | 37.1338 | 15.7921 | 24.1412 | 33.8293 | 125.874 |
| 1.9419 | 5.0 | 5000 | 1.8050 | 37.2569 | 15.8205 | 24.1969 | 34.0331 | 125.892 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6
|