---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bart-med-term-mlm
  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. -->

# bart-med-term-mlm

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2506
- Rouge2 Precision: 0.8338
- Rouge2 Recall: 0.6005
- Rouge2 Fmeasure: 0.6775

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.3426        | 1.0   | 15827 | 0.3029          | 0.8184           | 0.5913        | 0.6664          |
| 0.2911        | 2.0   | 31654 | 0.2694          | 0.8278           | 0.5963        | 0.6727          |
| 0.2571        | 3.0   | 47481 | 0.2549          | 0.8318           | 0.5985        | 0.6753          |
| 0.2303        | 4.0   | 63308 | 0.2506          | 0.8338           | 0.6005        | 0.6775          |


### Framework versions

- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.4
- Tokenizers 0.11.6