---
library_name: transformers
base_model: rosypossyyyy/bart-email-multitask
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-email-multitask
  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-email-multitask

This model is a fine-tuned version of [rosypossyyyy/bart-email-multitask](https://huggingface.co/rosypossyyyy/bart-email-multitask) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5448
- Rouge1: 51.01
- Rouge2: 36.53
- Rougel: 44.46
- Rougelsum: 44.91
- Gen Len: 53.5864

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.3719        | 0.1726 | 500  | 0.5641          | 49.82  | 35.56  | 43.37  | 43.9      | 55.6862 |
| 0.39          | 0.3452 | 1000 | 0.5499          | 50.66  | 36.17  | 44.07  | 44.56     | 53.0616 |
| 0.4325        | 0.5178 | 1500 | 0.5412          | 50.59  | 36.52  | 44.19  | 44.63     | 54.4194 |
| 0.4328        | 0.6904 | 2000 | 0.5556          | 50.8   | 36.6   | 44.19  | 44.7      | 54.1698 |
| 0.4133        | 0.8630 | 2500 | 0.5358          | 50.67  | 36.36  | 44.02  | 44.56     | 54.8808 |
| 0.3576        | 1.0356 | 3000 | 0.5371          | 51.14  | 36.78  | 44.59  | 45.09     | 53.4543 |
| 0.3878        | 1.2082 | 3500 | 0.5359          | 50.77  | 36.52  | 44.17  | 44.73     | 54.4243 |
| 0.3757        | 1.3808 | 4000 | 0.5294          | 50.76  | 36.73  | 44.34  | 44.9      | 54.2312 |


### Framework versions

- Transformers 4.57.5
- Pytorch 2.9.0+cu126
- Datasets 4.5.0
- Tokenizers 0.22.2