---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
model-index:
- name: finetuned-bartL-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. -->

# finetuned-bartL-samsum

This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3301

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.0651        | 0.2   | 1000  | 0.5671          |
| 0.4529        | 0.4   | 2000  | 0.4081          |
| 0.4316        | 0.6   | 3000  | 0.3714          |
| 0.4115        | 0.8   | 4000  | 0.3925          |
| 0.3922        | 1.0   | 5000  | 0.3621          |
| 0.3011        | 1.2   | 6000  | 0.3613          |
| 0.3129        | 1.4   | 7000  | 0.3482          |
| 0.2939        | 1.6   | 8000  | 0.3582          |
| 0.2931        | 1.8   | 9000  | 0.3388          |
| 0.2866        | 2.0   | 10000 | 0.3342          |
| 0.2095        | 2.2   | 11000 | 0.3379          |
| 0.2095        | 2.4   | 12000 | 0.3353          |
| 0.2068        | 2.6   | 13000 | 0.3335          |
| 0.2043        | 2.8   | 14000 | 0.3310          |
| 0.1961        | 3.0   | 15000 | 0.3301          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2