|
--- |
|
base_model: google/pegasus-large |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
- bleu |
|
model-index: |
|
- name: LifeSciencePegasusLargeModel |
|
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. --> |
|
|
|
# LifeSciencePegasusLargeModel |
|
|
|
This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 5.6523 |
|
- Rouge1: 44.7761 |
|
- Rouge2: 12.6726 |
|
- Rougel: 29.0847 |
|
- Rougelsum: 40.7566 |
|
- Bertscore Precision: 77.9283 |
|
- Bertscore Recall: 81.5854 |
|
- Bertscore F1: 79.7092 |
|
- Bleu: 0.0886 |
|
- Gen Len: 225.7220 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 | Bleu | Gen Len | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:| |
|
| 6.2586 | 0.2643 | 300 | 6.0453 | 40.1947 | 11.1082 | 26.9714 | 36.2747 | 76.6344 | 80.8385 | 78.6731 | 0.0775 | 225.7220 | |
|
| 6.0213 | 0.5286 | 600 | 5.7899 | 43.2445 | 12.1722 | 28.4564 | 39.1524 | 77.5194 | 81.3755 | 79.3945 | 0.0856 | 225.7220 | |
|
| 5.9018 | 0.7929 | 900 | 5.6523 | 44.7761 | 12.6726 | 29.0847 | 40.7566 | 77.9283 | 81.5854 | 79.7092 | 0.0886 | 225.7220 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.2.1 |
|
- Tokenizers 0.19.1 |
|
|
