|
--- |
|
license: apache-2.0 |
|
base_model: baek26/wiki_asp-animal_2910_bart-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: wiki_asp-animal_4639_wiki_asp-animal_2910_bart-base |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# wiki_asp-animal_4639_wiki_asp-animal_2910_bart-base |
|
|
|
This model is a fine-tuned version of [baek26/wiki_asp-animal_2910_bart-base](https://huggingface.co/baek26/wiki_asp-animal_2910_bart-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.5290 |
|
- Rouge1: 0.1446 |
|
- Rouge2: 0.0631 |
|
- Rougel: 0.1276 |
|
- Rougelsum: 0.1277 |
|
- Gen Len: 15.8808 |
|
|
|
## 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 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 64 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| No log | 1.93 | 500 | 2.5627 | 0.1435 | 0.0614 | 0.1262 | 0.1261 | 15.9017 | |
|
| No log | 3.87 | 1000 | 2.5538 | 0.1373 | 0.0583 | 0.121 | 0.1212 | 15.4998 | |
|
| No log | 5.8 | 1500 | 2.5393 | 0.1465 | 0.0638 | 0.1295 | 0.1297 | 16.0893 | |
|
| 2.3118 | 7.74 | 2000 | 2.5336 | 0.1517 | 0.0666 | 0.1336 | 0.1339 | 16.2204 | |
|
| 2.3118 | 9.67 | 2500 | 2.5290 | 0.1446 | 0.0631 | 0.1276 | 0.1277 | 15.8808 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.0.0+cu117 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|