---
library_name: peft
license: apache-2.0
base_model: google/roberta2roberta_L-24_cnn_daily_mail
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [google/roberta2roberta_L-24_cnn_daily_mail](https://huggingface.co/google/roberta2roberta_L-24_cnn_daily_mail) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7395
- Rouge1: 33.11
- Rouge2: 20.39
- Rougel: 27.32
- Rougelsum: 27.42
- Bertscore P: 87.57
- Bertscore R: 83.35
- Bertscore F1: 85.27

## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore P | Bertscore R | Bertscore F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-----------:|:-----------:|:------------:|
| 36.5558       | 0.8   | 20   | 7.8969          | 32.35  | 20.37  | 27.74  | 27.82     | 87.74       | 83.51       | 85.43        |
| 32.2661       | 1.6   | 40   | 7.0747          | 34.94  | 21.86  | 29.83  | 30.04     | 87.7        | 83.93       | 85.62        |
| 30.3129       | 2.4   | 60   | 6.7395          | 33.11  | 20.39  | 27.32  | 27.42     | 87.57       | 83.35       | 85.27        |


### Framework versions

- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0