---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-aeslc-rouge-3-loss-differentiable-100-cnt-supervised
  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-large-aeslc-rouge-3-loss-differentiable-100-cnt-supervised

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.9278
- Rouge1: 0.31
- Rouge2: 0.1577
- Rougel: 0.3039
- Rougelsum: 0.3036

## 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: 1e-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_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_ratio: 0.06
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 4.6006        | 1.56  | 20   | 5.0770          | 0.2559 | 0.1268 | 0.253  | 0.2529    |
| 2.9074        | 3.08  | 40   | 5.1504          | 0.2786 | 0.1408 | 0.2753 | 0.2752    |
| 2.2547        | 4.64  | 60   | 5.2866          | 0.2945 | 0.1433 | 0.289  | 0.2893    |
| 3.2227        | 6.16  | 80   | 5.9278          | 0.31   | 0.1577 | 0.3039 | 0.3036    |
| 1.7171        | 7.72  | 100  | 5.9767          | 0.3046 | 0.1471 | 0.2977 | 0.2978    |
| 1.5884        | 9.24  | 120  | 6.1892          | 0.2943 | 0.1416 | 0.2893 | 0.289     |
| 1.3678        | 10.8  | 140  | 6.4147          | 0.2908 | 0.1432 | 0.2844 | 0.2845    |
| 1.181         | 12.32 | 160  | 6.4444          | 0.2971 | 0.1476 | 0.2894 | 0.2892    |
| 1.0218        | 13.88 | 180  | 6.7040          | 0.2911 | 0.1423 | 0.2842 | 0.2835    |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1