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

# fine-tuned-led-base-book-summary

This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co./pszemraj/led-base-book-summary) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5918
- Rouge2 Precision: 0.0778
- Rouge2 Recall: 0.1291
- Rouge2 Fmeasure: 0.0958

## 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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 3.1612        | 0.4   | 150  | 2.7501          | 0.0605           | 0.1088        | 0.0764          |
| 2.9645        | 0.8   | 300  | 2.6528          | 0.0732           | 0.1251        | 0.0909          |
| 2.6754        | 1.19  | 450  | 2.6192          | 0.0752           | 0.1216        | 0.0917          |
| 2.8581        | 1.59  | 600  | 2.5968          | 0.0763           | 0.1239        | 0.0933          |
| 2.7604        | 1.99  | 750  | 2.5918          | 0.0778           | 0.1291        | 0.0958          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.14.1