---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bigData_w9
  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. -->

# bigData_w9

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0525
- Bleu4: 0.1309
- Rouge1: 0.4023
- Rouge2: 0.1845
- Rougel: 0.2757
- Rougelsum: 0.2753
- Gen Len: 76.4341

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 516
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu4  | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.0178        | 0.45  | 100  | 1.4840          | 0.1337 | 0.3875 | 0.1805 | 0.2688 | 0.2689    | 67.5509 |
| 1.142         | 0.89  | 200  | 1.1196          | 0.1296 | 0.3897 | 0.1766 | 0.2669 | 0.2667    | 69.3817 |
| 1.0693        | 1.34  | 300  | 1.0796          | 0.1345 | 0.3951 | 0.1818 | 0.2727 | 0.2727    | 70.015  |
| 1.0536        | 1.78  | 400  | 1.0684          | 0.1284 | 0.399  | 0.1839 | 0.2731 | 0.2729    | 77.3069 |
| 1.0084        | 2.23  | 500  | 1.0624          | 0.1287 | 0.3977 | 0.1808 | 0.2729 | 0.2729    | 76.7904 |
| 0.9855        | 2.67  | 600  | 1.0575          | 0.1349 | 0.4005 | 0.1843 | 0.2789 | 0.2787    | 72.4521 |
| 0.9812        | 3.12  | 700  | 1.0568          | 0.1303 | 0.4009 | 0.1847 | 0.2756 | 0.2752    | 76.1781 |
| 0.9916        | 3.56  | 800  | 1.0507          | 0.1364 | 0.4014 | 0.1853 | 0.279  | 0.2789    | 72.9746 |
| 0.9856        | 4.01  | 900  | 1.0507          | 0.1327 | 0.4003 | 0.1833 | 0.276  | 0.2758    | 74.9461 |
| 0.9747        | 4.45  | 1000 | 1.0519          | 0.1328 | 0.4014 | 0.185  | 0.276  | 0.2757    | 75.9461 |
| 0.9519        | 4.9   | 1100 | 1.0525          | 0.1309 | 0.4023 | 0.1845 | 0.2757 | 0.2753    | 76.4341 |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3