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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
|