transformers safetensors bart text2text-generation generated_from_trainer base_model:facebook/bart-base license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
model-index:
- name: bart-noised-with-kaggle-dist
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bart-noised-with-kaggle-dist

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: 0.2336

## 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: 5e-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
- lr_scheduler_warmup_steps: 10
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.4701        | 0.11  | 500   | 0.3771          |
| 0.3415        | 0.21  | 1000  | 0.3434          |
| 0.381         | 0.32  | 1500  | 0.3148          |
| 0.4196        | 0.43  | 2000  | 0.2986          |
| 0.3141        | 0.54  | 2500  | 0.3033          |
| 0.2984        | 0.64  | 3000  | 0.2834          |
| 0.2879        | 0.75  | 3500  | 0.2756          |
| 0.2906        | 0.86  | 4000  | 0.2646          |
| 0.346         | 0.96  | 4500  | 0.2594          |
| 0.2556        | 1.07  | 5000  | 0.2661          |
| 0.2264        | 1.18  | 5500  | 0.2611          |
| 0.2422        | 1.28  | 6000  | 0.2564          |
| 0.2103        | 1.39  | 6500  | 0.2543          |
| 0.2755        | 1.5   | 7000  | 0.2493          |
| 0.2587        | 1.61  | 7500  | 0.2473          |
| 0.2544        | 1.71  | 8000  | 0.2434          |
| 0.2136        | 1.82  | 8500  | 0.2383          |
| 0.2366        | 1.93  | 9000  | 0.2370          |
| 0.1862        | 2.03  | 9500  | 0.2455          |
| 0.1937        | 2.14  | 10000 | 0.2419          |
| 0.1673        | 2.25  | 10500 | 0.2405          |
| 0.1837        | 2.35  | 11000 | 0.2402          |
| 0.165         | 2.46  | 11500 | 0.2391          |
| 0.1725        | 2.57  | 12000 | 0.2352          |
| 0.1769        | 2.68  | 12500 | 0.2337          |
| 0.1347        | 2.78  | 13000 | 0.2355          |
| 0.1834        | 2.89  | 13500 | 0.2339          |
| 0.1505        | 3.0   | 14000 | 0.2336          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
