---
license: apache-2.0
base_model: matthew-mcc/google_summarization
tags:
- generated_from_trainer
model-index:
- name: google_summarization
  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. -->

# google_summarization

This model is a fine-tuned version of [matthew-mcc/google_summarization](https://huggingface.co/matthew-mcc/google_summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6378

## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.7453        | 1.0   | 1500  | 1.6085          |
| 1.5817        | 2.0   | 3000  | 1.5919          |
| 1.4864        | 3.0   | 4500  | 1.5984          |
| 1.3933        | 4.0   | 6000  | 1.6007          |
| 1.3403        | 5.0   | 7500  | 1.6159          |
| 1.2759        | 6.0   | 9000  | 1.6277          |
| 1.2191        | 7.0   | 10500 | 1.6324          |
| 1.208         | 8.0   | 12000 | 1.6378          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2