---
license: bsd-3-clause
base_model: pszemraj/led-base-book-summary
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: device
  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. -->

# device

This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co./pszemraj/led-base-book-summary) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0247
- Rouge1: 0.6269
- Rouge2: 0.3921
- Rougel: 0.5261
- Rougelsum: 0.5266
- Gen Len: 67.5584

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 274  | 1.0933          | 0.5918 | 0.3356 | 0.4785 | 0.4788    | 72.0547 |
| 1.1731        | 2.0   | 548  | 1.0177          | 0.5985 | 0.3525 | 0.4902 | 0.4906    | 68.5055 |
| 1.1731        | 3.0   | 822  | 0.9976          | 0.6063 | 0.3603 | 0.4982 | 0.4982    | 69.7263 |
| 0.7216        | 4.0   | 1096 | 0.9922          | 0.6113 | 0.3735 | 0.5081 | 0.5084    | 68.1861 |
| 0.7216        | 5.0   | 1370 | 0.9957          | 0.6193 | 0.3826 | 0.5216 | 0.5217    | 65.4617 |
| 0.5252        | 6.0   | 1644 | 1.0127          | 0.6252 | 0.3877 | 0.5231 | 0.5236    | 68.0584 |
| 0.5252        | 7.0   | 1918 | 1.0221          | 0.6252 | 0.3897 | 0.5246 | 0.5246    | 67.5931 |
| 0.4079        | 8.0   | 2192 | 1.0247          | 0.6269 | 0.3921 | 0.5261 | 0.5266    | 67.5584 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1