---
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: 0.6511
- Rouge1: 0.35
- Rouge2: 0.2527
- Rougel: 0.3229
- Rougelsum: 0.323
- 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   | 3.3125          | 0.2888 | 0.1482 | 0.2448 | 0.2454    | 20.0    |
| No log        | 2.0   | 54   | 2.2699          | 0.2926 | 0.1667 | 0.2564 | 0.2574    | 20.0    |
| No log        | 3.0   | 81   | 1.7686          | 0.3119 | 0.1908 | 0.2752 | 0.2753    | 20.0    |
| No log        | 4.0   | 108  | 1.3882          | 0.324  | 0.2104 | 0.2937 | 0.2939    | 20.0    |
| No log        | 5.0   | 135  | 1.1275          | 0.3151 | 0.2061 | 0.2871 | 0.2877    | 20.0    |
| No log        | 6.0   | 162  | 0.9372          | 0.3293 | 0.2231 | 0.3017 | 0.3022    | 20.0    |
| No log        | 7.0   | 189  | 0.8252          | 0.33   | 0.2182 | 0.2982 | 0.2988    | 20.0    |
| No log        | 8.0   | 216  | 0.7575          | 0.3378 | 0.2317 | 0.3058 | 0.3065    | 20.0    |
| No log        | 9.0   | 243  | 0.7102          | 0.3498 | 0.2418 | 0.3148 | 0.3149    | 20.0    |
| No log        | 10.0  | 270  | 0.6890          | 0.3411 | 0.2374 | 0.3119 | 0.3126    | 20.0    |
| No log        | 11.0  | 297  | 0.6760          | 0.3441 | 0.2394 | 0.3151 | 0.3155    | 20.0    |
| No log        | 12.0  | 324  | 0.6640          | 0.3442 | 0.2417 | 0.3151 | 0.3152    | 20.0    |
| No log        | 13.0  | 351  | 0.6520          | 0.3548 | 0.2506 | 0.3242 | 0.3246    | 20.0    |
| No log        | 14.0  | 378  | 0.6519          | 0.3497 | 0.2506 | 0.3199 | 0.3201    | 20.0    |
| No log        | 15.0  | 405  | 0.6511          | 0.35   | 0.2527 | 0.3229 | 0.323     | 20.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0