license: cc-by-nc-sa-4.0 | |
tags: | |
- generated_from_trainer | |
- longt5 | |
- summarization | |
model-index: | |
- name: longt5-mediasum | |
results: | |
- task: | |
type: summarization | |
name: Summarization | |
dataset: | |
name: xsum | |
type: xsum | |
config: default | |
split: test | |
metrics: | |
- name: ROUGE-1 | |
type: rouge | |
value: 22.7044 | |
verified: true | |
- name: ROUGE-2 | |
type: rouge | |
value: 5.616 | |
verified: true | |
- name: ROUGE-L | |
type: rouge | |
value: 18.0111 | |
verified: true | |
- name: ROUGE-LSUM | |
type: rouge | |
value: 18.1554 | |
verified: true | |
- name: loss | |
type: loss | |
value: 2.1656227111816406 | |
verified: true | |
- name: gen_len | |
type: gen_len | |
value: 18.3527 | |
verified: true | |
<!-- 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. --> | |
# longt5-mediasum | |
This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 2.0129 | |
## 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: 12 | |
- eval_batch_size: 16 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- lr_scheduler_warmup_ratio: 0.1 | |
- num_epochs: 3.0 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | | |
|:-------------:|:-----:|:----:|:---------------:| | |
| 2.66 | 1.0 | 1667 | 2.0643 | | |
| 2.472 | 2.0 | 3334 | 2.0241 | | |
| 2.3574 | 3.0 | 5001 | 2.0129 | | |
### Framework versions | |
- Transformers 4.20.1 | |
- Pytorch 1.11.0a0+17540c5 | |
- Datasets 2.3.2 | |
- Tokenizers 0.12.1 | |