---
license: apache-2.0
base_model: sshleifer/distilbart-xsum-12-6
tags:
- generated_from_trainer
model-index:
- name: bart-abs-1509-0313-lr-0.0003-bs-2-maxep-10
  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-abs-1509-0313-lr-0.0003-bs-2-maxep-10

This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-6](https://huggingface.co/sshleifer/distilbart-xsum-12-6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 7.6999
- Rouge/rouge1: 0.2439
- Rouge/rouge2: 0.0504
- Rouge/rougel: 0.2065
- Rouge/rougelsum: 0.2067
- Bertscore/bertscore-precision: 0.8544
- Bertscore/bertscore-recall: 0.8581
- Bertscore/bertscore-f1: 0.8562
- Meteor: 0.229
- Gen Len: 44.0

## 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: 0.0003
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge/rouge1 | Rouge/rouge2 | Rouge/rougel | Rouge/rougelsum | Bertscore/bertscore-precision | Bertscore/bertscore-recall | Bertscore/bertscore-f1 | Meteor | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-----------------------------:|:--------------------------:|:----------------------:|:------:|:-------:|
| 2.1693        | 1.0   | 434  | 4.5206          | 0.2693       | 0.0703       | 0.2315       | 0.232           | 0.8864                        | 0.8585                     | 0.8722                 | 0.2188 | 29.0    |
| 1.3403        | 2.0   | 868  | 5.0395          | 0.3061       | 0.0778       | 0.251        | 0.2513          | 0.8875                        | 0.864                      | 0.8755                 | 0.239  | 32.0    |
| 1.1783        | 3.0   | 1302 | 5.1339          | 0.2426       | 0.0523       | 0.1835       | 0.1835          | 0.8501                        | 0.8566                     | 0.8533                 | 0.248  | 52.0    |
| 0.8203        | 4.0   | 1736 | 5.6678          | 0.3347       | 0.0996       | 0.2675       | 0.2678          | 0.8793                        | 0.8662                     | 0.8727                 | 0.2663 | 27.0    |
| 0.623         | 5.0   | 2170 | 6.1732          | 0.2961       | 0.0668       | 0.2313       | 0.2314          | 0.8628                        | 0.8608                     | 0.8617                 | 0.2421 | 52.0    |
| 0.5051        | 6.0   | 2604 | 6.1011          | 0.2953       | 0.0542       | 0.2213       | 0.2211          | 0.8685                        | 0.8588                     | 0.8636                 | 0.2403 | 34.0    |
| 0.4004        | 7.0   | 3038 | 6.8848          | 0.2613       | 0.0803       | 0.214        | 0.2142          | 0.8711                        | 0.8469                     | 0.8588                 | 0.2102 | 26.0    |
| 0.3371        | 8.0   | 3472 | 7.2987          | 0.2132       | 0.0353       | 0.1717       | 0.1717          | 0.8605                        | 0.8522                     | 0.8563                 | 0.1839 | 27.0    |
| 0.2954        | 9.0   | 3906 | 7.4692          | 0.244        | 0.063        | 0.1986       | 0.1986          | 0.8544                        | 0.8608                     | 0.8575                 | 0.211  | 52.0    |
| 0.2576        | 10.0  | 4340 | 7.6999          | 0.2439       | 0.0504       | 0.2065       | 0.2067          | 0.8544                        | 0.8581                     | 0.8562                 | 0.229  | 44.0    |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1