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---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: LifeScienceBARTMainSections
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. -->
# LifeScienceBARTMainSections
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7019
- Rouge1: 49.0793
- Rouge2: 14.8566
- Rougel: 33.334
- Rougelsum: 45.7662
- Bertscore Precision: 81.188
- Bertscore Recall: 82.9404
- Bertscore F1: 82.0519
- Bleu: 0.1030
- Gen Len: 229.2407
## 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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------------------:|:----------------:|:------------:|:------:|:--------:|
| 6.4111 | 0.0888 | 100 | 6.3840 | 40.091 | 10.5597 | 26.7276 | 37.4414 | 78.1353 | 80.7026 | 79.3933 | 0.0735 | 229.2407 |
| 6.0433 | 0.1776 | 200 | 5.8904 | 41.0419 | 10.8596 | 27.756 | 38.5185 | 78.0408 | 80.8161 | 79.3991 | 0.0767 | 229.2407 |
| 5.6541 | 0.2664 | 300 | 5.5687 | 41.4629 | 11.3685 | 28.1111 | 38.5646 | 77.836 | 81.223 | 79.4878 | 0.0802 | 229.2407 |
| 5.4974 | 0.3552 | 400 | 5.3592 | 46.3384 | 12.5596 | 30.1004 | 43.0989 | 79.7577 | 81.8421 | 80.7827 | 0.0866 | 229.2407 |
| 5.3027 | 0.4440 | 500 | 5.1945 | 45.5757 | 12.693 | 30.676 | 42.4402 | 79.9319 | 81.977 | 80.9379 | 0.0883 | 229.2407 |
| 5.1618 | 0.5328 | 600 | 5.0456 | 46.1671 | 13.2513 | 31.2648 | 43.2104 | 80.1208 | 82.2358 | 81.161 | 0.0917 | 229.2407 |
| 5.0999 | 0.6216 | 700 | 4.9409 | 47.7896 | 14.2812 | 32.3827 | 44.2521 | 80.5408 | 82.6162 | 81.5619 | 0.0995 | 229.2407 |
| 4.971 | 0.7104 | 800 | 4.8510 | 47.59 | 14.1292 | 32.5959 | 44.307 | 80.6111 | 82.6499 | 81.6143 | 0.0988 | 229.2407 |
| 4.8843 | 0.7992 | 900 | 4.7847 | 49.0909 | 14.5478 | 33.0067 | 45.5964 | 81.0221 | 82.8266 | 81.9112 | 0.1013 | 229.2407 |
| 4.8264 | 0.8880 | 1000 | 4.7379 | 48.6746 | 14.6309 | 33.1973 | 45.4536 | 81.0718 | 82.8574 | 81.9519 | 0.1012 | 229.2407 |
| 4.8295 | 0.9767 | 1100 | 4.7019 | 49.0793 | 14.8566 | 33.334 | 45.7662 | 81.188 | 82.9404 | 82.0519 | 0.1030 | 229.2407 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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