---
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: 0.6537
- Rouge1: 0.3618
- Rouge2: 0.2634
- Rougel: 0.3348
- Rougelsum: 0.336
- 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   | 3.3018          | 0.2994 | 0.1537 | 0.2528 | 0.2525    | 20.0    |
| No log        | 2.0   | 54   | 2.2697          | 0.3287 | 0.1959 | 0.286  | 0.2866    | 20.0    |
| No log        | 3.0   | 81   | 1.7739          | 0.3265 | 0.2103 | 0.2947 | 0.2954    | 20.0    |
| No log        | 4.0   | 108  | 1.4085          | 0.3257 | 0.2128 | 0.2931 | 0.2937    | 20.0    |
| No log        | 5.0   | 135  | 1.1230          | 0.3458 | 0.2307 | 0.3116 | 0.3124    | 20.0    |
| No log        | 6.0   | 162  | 0.9408          | 0.3448 | 0.2371 | 0.3129 | 0.3139    | 20.0    |
| No log        | 7.0   | 189  | 0.8269          | 0.3502 | 0.2479 | 0.3201 | 0.3212    | 20.0    |
| No log        | 8.0   | 216  | 0.7584          | 0.3442 | 0.2434 | 0.3145 | 0.3157    | 20.0    |
| No log        | 9.0   | 243  | 0.7075          | 0.3606 | 0.2619 | 0.3329 | 0.3339    | 20.0    |
| No log        | 10.0  | 270  | 0.6890          | 0.3508 | 0.2517 | 0.3208 | 0.3219    | 20.0    |
| No log        | 11.0  | 297  | 0.6761          | 0.3501 | 0.2483 | 0.3215 | 0.3228    | 20.0    |
| No log        | 12.0  | 324  | 0.6631          | 0.3532 | 0.2522 | 0.3237 | 0.3245    | 20.0    |
| No log        | 13.0  | 351  | 0.6573          | 0.3625 | 0.2661 | 0.3358 | 0.3372    | 20.0    |
| No log        | 14.0  | 378  | 0.6528          | 0.3594 | 0.2608 | 0.3322 | 0.3333    | 20.0    |
| No log        | 15.0  | 405  | 0.6537          | 0.3618 | 0.2634 | 0.3348 | 0.336     | 20.0    |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1