metadata
license: apache-2.0
tags:
- summarization
metrics:
- rouge
model-index:
- name: POCTS
results:
- task:
name: Summarization
type: summarization
metrics:
- name: Rouge1
type: rouge
value: 26.1391
POCTS
This model is a fine-tuned version of facebook/bart-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0970
- Rouge1: 26.1391
- Rouge2: 7.3101
- Rougel: 19.1217
- Rougelsum: 21.9706
- Gen Len: 46.2245
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
- lr_scheduler_warmup_ratio: 0.15
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.3259 | 1.0 | 33875 | 3.2535 | 17.942 | 4.5143 | 14.2766 | 15.582 | 19.3901 |
| 2.9764 | 2.0 | 67750 | 3.1278 | 18.6558 | 5.1844 | 15.0939 | 16.3367 | 19.9174 |
| 2.5889 | 3.0 | 101625 | 3.0970 | 19.1763 | 5.4517 | 15.5342 | 16.7186 | 19.8855 |
Framework versions
- Transformers 4.10.2
- Pytorch 1.7.1+cu110
- Datasets 1.11.0
- Tokenizers 0.10.3