---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: all_9843_bart-base
  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. -->

# all_9843_bart-base

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2356
- Rouge1: 0.2722
- Rouge2: 0.1239
- Rougel: 0.2315
- Rougelsum: 0.2424
- Gen Len: 19.9567

## 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-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.759         | 0.89  | 500  | 1.2348          | 0.2615 | 0.1071 | 0.2187 | 0.2283    | 19.956  |
| 1.0891        | 1.78  | 1000 | 1.2122          | 0.2667 | 0.1145 | 0.224  | 0.2351    | 19.9713 |
| 0.9877        | 2.67  | 1500 | 1.2076          | 0.2701 | 0.118  | 0.2271 | 0.238     | 19.9413 |
| 0.9299        | 3.56  | 2000 | 1.2072          | 0.2682 | 0.1205 | 0.2267 | 0.2385    | 19.9667 |
| 0.8841        | 4.44  | 2500 | 1.2088          | 0.2711 | 0.1213 | 0.2294 | 0.2406    | 19.956  |
| 0.8425        | 5.33  | 3000 | 1.2154          | 0.2718 | 0.1245 | 0.2317 | 0.2426    | 19.9673 |
| 0.8123        | 6.22  | 3500 | 1.2276          | 0.2719 | 0.1242 | 0.2315 | 0.2422    | 19.958  |
| 0.7876        | 7.11  | 4000 | 1.2259          | 0.2726 | 0.1228 | 0.2311 | 0.242     | 19.9647 |
| 0.769         | 8.0   | 4500 | 1.2244          | 0.2733 | 0.126  | 0.2324 | 0.2436    | 19.9667 |
| 0.75          | 8.89  | 5000 | 1.2313          | 0.2723 | 0.1236 | 0.231  | 0.2422    | 19.964  |
| 0.7369        | 9.78  | 5500 | 1.2356          | 0.2722 | 0.1239 | 0.2315 | 0.2424    | 19.9567 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2