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---
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
|