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

This model is a fine-tuned version of [gayanin/bart-noised-with-gcd-dist](https://huggingface.co/gayanin/bart-noised-with-gcd-dist) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2281

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.2582        | 0.11  | 500   | 0.2439          |
| 0.2496        | 0.21  | 1000  | 0.2384          |
| 0.2469        | 0.32  | 1500  | 0.2428          |
| 0.2786        | 0.43  | 2000  | 0.2409          |
| 0.195         | 0.54  | 2500  | 0.2409          |
| 0.2615        | 0.64  | 3000  | 0.2352          |
| 0.2593        | 0.75  | 3500  | 0.2359          |
| 0.2472        | 0.86  | 4000  | 0.2340          |
| 0.2762        | 0.96  | 4500  | 0.2285          |
| 0.181         | 1.07  | 5000  | 0.2374          |
| 0.1963        | 1.18  | 5500  | 0.2345          |
| 0.1848        | 1.28  | 6000  | 0.2378          |
| 0.181         | 1.39  | 6500  | 0.2343          |
| 0.2063        | 1.5   | 7000  | 0.2299          |
| 0.1774        | 1.61  | 7500  | 0.2302          |
| 0.2058        | 1.71  | 8000  | 0.2267          |
| 0.2256        | 1.82  | 8500  | 0.2262          |
| 0.1661        | 1.93  | 9000  | 0.2265          |
| 0.1475        | 2.03  | 9500  | 0.2327          |
| 0.1229        | 2.14  | 10000 | 0.2338          |
| 0.1484        | 2.25  | 10500 | 0.2326          |
| 0.1679        | 2.35  | 11000 | 0.2326          |
| 0.1278        | 2.46  | 11500 | 0.2312          |
| 0.143         | 2.57  | 12000 | 0.2291          |
| 0.1331        | 2.68  | 12500 | 0.2284          |
| 0.1504        | 2.78  | 13000 | 0.2289          |
| 0.1308        | 2.89  | 13500 | 0.2293          |
| 0.1657        | 3.0   | 14000 | 0.2281          |


### Framework versions

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