---
license: apache-2.0
base_model: ainize/bart-base-cnn
tags:
- generated_from_trainer
model-index:
- name: bart-samsum
  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-samsum

This model is a fine-tuned version of [ainize/bart-base-cnn](https://huggingface.co/ainize/bart-base-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4587

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.2901        | 0.64  | 500   | 1.2203          |
| 1.2057        | 1.28  | 1000  | 1.1384          |
| 1.1364        | 1.93  | 1500  | 1.1225          |
| 0.9711        | 2.57  | 2000  | 1.1362          |
| 0.786         | 3.21  | 2500  | 1.1461          |
| 0.818         | 3.85  | 3000  | 1.1298          |
| 0.7135        | 4.49  | 3500  | 1.1666          |
| 0.6222        | 5.14  | 4000  | 1.2114          |
| 0.64          | 5.78  | 4500  | 1.2103          |
| 0.5272        | 6.42  | 5000  | 1.2571          |
| 0.5057        | 7.06  | 5500  | 1.2963          |
| 0.4917        | 7.7   | 6000  | 1.2937          |
| 0.4291        | 8.35  | 6500  | 1.3286          |
| 0.4171        | 8.99  | 7000  | 1.3125          |
| 0.418         | 9.63  | 7500  | 1.3516          |
| 0.3576        | 10.27 | 8000  | 1.3778          |
| 0.3736        | 10.91 | 8500  | 1.3847          |
| 0.3443        | 11.56 | 9000  | 1.4215          |
| 0.2952        | 12.2  | 9500  | 1.4324          |
| 0.3236        | 12.84 | 10000 | 1.4355          |
| 0.2978        | 13.48 | 10500 | 1.4473          |
| 0.2828        | 14.13 | 11000 | 1.4557          |
| 0.304         | 14.77 | 11500 | 1.4587          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3