---
library_name: transformers
base_model: tarekziade/wikipedia-summaries-t5-efficient-tiny
tags:
- generated_from_trainer
model-index:
- name: t5-efficient-tiny-nh8-summarizer
  results: []
datasets:
- shorecode/summary-collection-60k-rows
---

<!-- 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. -->

# t5-efficient-tiny-summarizer-general-purpose

This model is a fine-tuned version of [tarekziade/wikipedia-summaries-t5-efficient-tiny](https://huggingface.co./tarekziade/wikipedia-summaries-t5-efficient-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan

## 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: 3.0000000000000004e-05
- train_batch_size: 63
- eval_batch_size: 63
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0           | 0.2096 | 200  | nan             |
| 0.0           | 0.4193 | 400  | nan             |
| 0.0           | 0.6289 | 600  | nan             |
| 0.0           | 0.8386 | 800  | nan             |
| 0.0           | 1.0482 | 1000 | nan             |
| 0.0           | 1.2579 | 1200 | nan             |
| 0.0           | 1.4675 | 1400 | nan             |
| 0.0           | 1.6771 | 1600 | nan             |
| 0.0           | 1.8868 | 1800 | nan             |
| 0.0           | 2.0964 | 2000 | nan             |
| 0.0           | 2.3061 | 2200 | nan             |
| 0.0           | 2.5157 | 2400 | nan             |
| 0.0           | 2.7254 | 2600 | nan             |
| 0.0           | 2.9350 | 2800 | nan             |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.21.0