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---
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: finetuned_bartbase_on_medi_data
results: []
datasets:
- amagastya/medical-abstract-summaries
language:
- en
pipeline_tag: summarization
---
<!-- 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. -->
# finetuned_bartbase_on_medi_data
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: 0.1259
- Rouge1: 0.8208
- Rouge2: 0.6644
- Rougel: 0.7467
- Rougelsum: 0.7542
- Gen Len: 75.0167
## 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: 2.660730299084495e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 175 | 0.1297 | 0.812 | 0.6479 | 0.7393 | 0.7477 | 76.0533 |
| No log | 2.0 | 350 | 0.1037 | 0.817 | 0.6546 | 0.7393 | 0.7497 | 77.2933 |
| 0.0519 | 3.0 | 525 | 0.1095 | 0.8196 | 0.6656 | 0.7504 | 0.7588 | 75.38 |
| 0.0519 | 4.0 | 700 | 0.1157 | 0.8141 | 0.6539 | 0.7397 | 0.7494 | 76.3633 |
| 0.0519 | 5.0 | 875 | 0.1259 | 0.8208 | 0.6644 | 0.7467 | 0.7542 | 75.0167 |
### Framework versions
- Transformers 4.30.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3 |