---
library_name: transformers
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-reddit_tifu-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
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# bart-large-reddit_tifu-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: 3.2227
- Rouge1: 0.2709
- Rouge2: 0.0801
- Rougel: 0.2095
- Rougelsum: 0.2094

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 4.0348        | 0.8   | 20   | 3.2038          | 0.1599 | 0.0287 | 0.1106 | 0.1106    |
| 3.1204        | 1.6   | 40   | 2.8897          | 0.2148 | 0.059  | 0.1674 | 0.1675    |
| 2.7132        | 2.4   | 60   | 2.8857          | 0.2646 | 0.0812 | 0.2047 | 0.2045    |
| 2.5367        | 3.2   | 80   | 2.8879          | 0.2505 | 0.0741 | 0.1974 | 0.1974    |
| 2.1373        | 4.0   | 100  | 3.2227          | 0.2709 | 0.0801 | 0.2095 | 0.2094    |
| 1.9878        | 4.8   | 120  | 3.1669          | 0.2582 | 0.0737 | 0.1972 | 0.1973    |
| 1.6781        | 5.6   | 140  | 3.2703          | 0.2467 | 0.0696 | 0.1962 | 0.1963    |
| 1.2597        | 6.4   | 160  | 3.2969          | 0.2261 | 0.0544 | 0.1792 | 0.1792    |


### Framework versions

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