metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: resume6
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
config: default
split: test
args: default
metrics:
- name: Rouge1
type: rouge
value: 22.17621046093242
resume6
This model is a fine-tuned version of AKbuyer/resume5 on the multi_news dataset. It achieves the following results on the evaluation set:
- Loss: 2.9796
- Rouge1: 22.1762
- Rouge2: 6.6459
- Rougel: 18.3710
- Rougelsum: 18.3626
- Gen Len: 1893.4899
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-07
- 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: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.3348 | 1.0 | 5622 | 3.0918 | 21.3362 | 6.1922 | 17.7104 | 17.6992 | 1893.0630 |
| 3.2854 | 2.0 | 11244 | 3.0466 | 21.6506 | 6.3791 | 17.9362 | 17.9246 | 1891.6044 |
| 3.2205 | 3.0 | 16866 | 3.0200 | 21.8475 | 6.4847 | 18.0981 | 18.0882 | 1892.4760 |
| 3.2251 | 4.0 | 22488 | 3.0029 | 22.0082 | 6.5196 | 18.2405 | 18.2301 | 1892.9385 |
| 3.2348 | 5.0 | 28110 | 2.9916 | 22.1078 | 6.5975 | 18.3134 | 18.2985 | 1893.3298 |
| 3.2257 | 6.0 | 33732 | 2.9845 | 22.1627 | 6.6119 | 18.3677 | 18.3496 | 1893.5788 |
| 3.2106 | 7.0 | 39354 | 2.9806 | 22.1825 | 6.6472 | 18.3798 | 18.3664 | 1893.5432 |
| 3.22 | 8.0 | 44976 | 2.9796 | 22.1762 | 6.6459 | 18.3710 | 18.3626 | 1893.4899 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3