|
--- |
|
license: apache-2.0 |
|
base_model: allenai/led-base-16384 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- big_patent |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: led-base-big-patent |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: big_patent |
|
type: big_patent |
|
config: g |
|
split: validation |
|
args: g |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 0.2658 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# led-base-big-patent |
|
|
|
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the big_patent dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2665 |
|
- Rouge1: 0.2658 |
|
- Rouge2: 0.1008 |
|
- Rougel: 0.2231 |
|
- Rougelsum: 0.2244 |
|
- Gen Len: 19.6593 |
|
|
|
## 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: 4.892476e-05 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 4 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| No log | 1.0 | 108 | 0.2940 | 0.2525 | 0.0809 | 0.2062 | 0.2074 | 19.956 | |
|
| No log | 2.0 | 216 | 0.2595 | 0.2713 | 0.097 | 0.2233 | 0.2256 | 19.5165 | |
|
| No log | 3.0 | 324 | 0.2665 | 0.2658 | 0.1008 | 0.2231 | 0.2244 | 19.6593 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
