metadata
license: bsd-3-clause
tags:
- generated_from_trainer
datasets:
- pszemraj/scientific_lay_summarisation-plos-norm
metrics:
- rouge
model-index:
- name: >-
long-t5-tglobal-xl-16384-book-summary-scientific_lay_summarisation-plos-norm-16384-summ-v1
results:
- task:
name: Summarization
type: summarization
dataset:
name: pszemraj/scientific_lay_summarisation-plos-norm
type: pszemraj/scientific_lay_summarisation-plos-norm
split: validation
metrics:
- name: Rouge1
type: rouge
value: 44.3203
long-t5-tglobal-xl-16384-book-summary-scientific_lay_summarisation-plos-norm-16384-summ-v1
This model is a fine-tuned version of pszemraj/long-t5-tglobal-xl-16384-book-summary on the pszemraj/scientific_lay_summarisation-plos-norm dataset. It achieves the following results on the evaluation set:
- Loss: 1.5041
- Rouge1: 44.3203
- Rouge2: 11.0576
- Rougel: 22.7584
- Rougelsum: 40.1462
- Gen Len: 256.66
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: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 165
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.7715 | 0.28 | 350 | 1.5310 | 43.4729 | 10.4616 | 22.1928 | 39.505 | 260.87 |
| 1.9307 | 0.56 | 700 | 1.5102 | 44.1634 | 10.9336 | 22.3896 | 40.2939 | 253.58 |
| 1.2981 | 0.84 | 1050 | 1.5046 | 44.2728 | 10.8455 | 22.4122 | 40.3019 | 261.29 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3