|
--- |
|
tags: |
|
- summarization |
|
- summary |
|
- booksum |
|
- long-document |
|
- long-form |
|
- lsg |
|
datasets: |
|
- kmfoda/booksum |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: ccdv/lsg-bart-base-4096-booksum |
|
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. --> |
|
|
|
**This model relies on a custom modeling file, you need to add trust_remote_code=True**\ |
|
**See [\#13467](https://github.com/huggingface/transformers/pull/13467)** |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("ccdv/lsg-bart-base-4096-booksum", trust_remote_code=True) |
|
model = AutoModelForSeq2SeqLM.from_pretrained("ccdv/lsg-bart-base-4096-booksum", trust_remote_code=True) |
|
|
|
text = "Replace by what you want." |
|
pipe = pipeline("text2text-generation", model=model, tokenizer=tokenizer, device=0) |
|
generated_text = pipe( |
|
text, |
|
truncation=True, |
|
max_length=64, |
|
no_repeat_ngram_size=7, |
|
num_beams=2, |
|
early_stopping=True |
|
) |
|
``` |
|
|
|
# ccdv/lsg-bart-base-4096-booksum |
|
|
|
This model is a fine-tuned version of [ccdv/lsg-bart-base-4096](https://huggingface.co/ccdv/lsg-bart-base-4096) on the kmfoda/booksum kmfoda--booksum dataset. |
|
It achieves the following results on the evaluation set: |
|
- eval_loss: 3.2654 |
|
- eval_rouge1: 33.9468 |
|
- eval_rouge2: 6.7034 |
|
- eval_rougeL: 16.7879 |
|
- eval_rougeLsum: 31.7677 |
|
- eval_gen_len: 427.6918 |
|
- eval_runtime: 2910.3841 |
|
- eval_samples_per_second: 0.492 |
|
- eval_steps_per_second: 0.062 |
|
- eval_samples: 1431 |
|
|
|
## 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: 8e-05 |
|
- train_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 30.0 |
|
|
|
|
|
### Generate hyperparameters |
|
|
|
The following hyperparameters were used during generation: |
|
|
|
- dataset_name: kmfoda/booksum |
|
- dataset_config_name: kmfoda--booksum |
|
- eval_batch_size: 8 |
|
- eval_samples: 1431 |
|
- early_stopping: True |
|
- ignore_pad_token_for_loss: True |
|
- length_penalty: 2.0 |
|
- max_length: 512 |
|
- min_length: 128 |
|
- num_beams: 5 |
|
- no_repeat_ngram_size: None |
|
- seed: 123 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.23.1 |
|
- Pytorch 1.12.1 |
|
- Datasets 2.3.2 |
|
- Tokenizers 0.11.6 |
|
|