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

# BARTModel_for_Ecommerce

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: 0.6400
- Rouge1: 0.3515
- Rouge2: 0.2381
- Rougel: 0.3187
- Rougelsum: 0.3187
- Gen Len: 20.0

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 27   | 3.5206          | 0.3072 | 0.1595 | 0.26   | 0.26      | 20.0    |
| No log        | 2.0   | 54   | 2.3786          | 0.3139 | 0.1747 | 0.268  | 0.2681    | 20.0    |
| No log        | 3.0   | 81   | 1.8443          | 0.3328 | 0.2038 | 0.2924 | 0.2932    | 20.0    |
| No log        | 4.0   | 108  | 1.4537          | 0.3276 | 0.2076 | 0.2887 | 0.2892    | 20.0    |
| No log        | 5.0   | 135  | 1.1480          | 0.3301 | 0.212  | 0.292  | 0.2924    | 20.0    |
| No log        | 6.0   | 162  | 0.9457          | 0.3465 | 0.2292 | 0.3084 | 0.3091    | 20.0    |
| No log        | 7.0   | 189  | 0.8317          | 0.345  | 0.2253 | 0.3074 | 0.3078    | 20.0    |
| No log        | 8.0   | 216  | 0.7544          | 0.3456 | 0.2293 | 0.3121 | 0.3124    | 20.0    |
| No log        | 9.0   | 243  | 0.7076          | 0.3601 | 0.246  | 0.3278 | 0.3276    | 20.0    |
| No log        | 10.0  | 270  | 0.6817          | 0.3464 | 0.2358 | 0.3139 | 0.3139    | 20.0    |
| No log        | 11.0  | 297  | 0.6609          | 0.3586 | 0.2407 | 0.3235 | 0.3241    | 20.0    |
| No log        | 12.0  | 324  | 0.6557          | 0.3563 | 0.2432 | 0.3226 | 0.3227    | 20.0    |
| No log        | 13.0  | 351  | 0.6451          | 0.3511 | 0.238  | 0.3192 | 0.3195    | 20.0    |
| No log        | 14.0  | 378  | 0.6430          | 0.3516 | 0.2385 | 0.3182 | 0.3183    | 20.0    |
| No log        | 15.0  | 405  | 0.6400          | 0.3515 | 0.2381 | 0.3187 | 0.3187    | 20.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0