transformers safetensors bart text2text-generation generated_from_trainer base_model:gayanin/bart-noised-with-babylon-dist license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: gayanin/bart-noised-with-babylon-dist
tags:
- generated_from_trainer
model-index:
- name: bart-noised-with-babylon-kaggle-dist
  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. -->

# bart-noised-with-babylon-kaggle-dist

This model is a fine-tuned version of [gayanin/bart-noised-with-babylon-dist](https://huggingface.co/gayanin/bart-noised-with-babylon-dist) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2232

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.256         | 0.11  | 500   | 0.2499          |
| 0.2325        | 0.21  | 1000  | 0.2487          |
| 0.2694        | 0.32  | 1500  | 0.2387          |
| 0.2936        | 0.43  | 2000  | 0.2389          |
| 0.2341        | 0.54  | 2500  | 0.2452          |
| 0.2204        | 0.64  | 3000  | 0.2349          |
| 0.2162        | 0.75  | 3500  | 0.2395          |
| 0.2299        | 0.86  | 4000  | 0.2291          |
| 0.2975        | 0.96  | 4500  | 0.2258          |
| 0.2064        | 1.07  | 5000  | 0.2344          |
| 0.1681        | 1.18  | 5500  | 0.2324          |
| 0.1915        | 1.28  | 6000  | 0.2364          |
| 0.159         | 1.39  | 6500  | 0.2332          |
| 0.2176        | 1.5   | 7000  | 0.2278          |
| 0.2139        | 1.61  | 7500  | 0.2264          |
| 0.1988        | 1.71  | 8000  | 0.2263          |
| 0.1744        | 1.82  | 8500  | 0.2236          |
| 0.1848        | 1.93  | 9000  | 0.2207          |
| 0.1652        | 2.03  | 9500  | 0.2298          |
| 0.1571        | 2.14  | 10000 | 0.2278          |
| 0.1241        | 2.25  | 10500 | 0.2257          |
| 0.1409        | 2.35  | 11000 | 0.2278          |
| 0.125         | 2.46  | 11500 | 0.2258          |
| 0.1373        | 2.57  | 12000 | 0.2253          |
| 0.1371        | 2.68  | 12500 | 0.2237          |
| 0.1088        | 2.78  | 13000 | 0.2249          |
| 0.1464        | 2.89  | 13500 | 0.2231          |
| 0.121         | 3.0   | 14000 | 0.2232          |


### Framework versions

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