---
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-10-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-10-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: 5.1776
- Rouge1: 0.2418
- Rouge2: 0.1239
- Rougel: 0.2314
- Rougelsum: 0.2311

## 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: 2
- total_train_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.8234        | 3.4   | 10   | 5.0940          | 0.2049 | 0.1039 | 0.1952 | 0.1954    |
| 1.7867        | 6.8   | 20   | 5.1776          | 0.2418 | 0.1239 | 0.2314 | 0.2311    |
| 1.3308        | 10.0  | 30   | 5.4160          | 0.2345 | 0.1139 | 0.2216 | 0.2215    |
| 0.7055        | 13.4  | 40   | 5.7111          | 0.236  | 0.1141 | 0.2235 | 0.2235    |
| 0.5036        | 16.8  | 50   | 5.9660          | 0.2347 | 0.1118 | 0.2221 | 0.2222    |


### Framework versions

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