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---
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
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