transformers safetensors t5 text2text-generation generated_from_trainer base_model:OmarHaroon01/t5_pretrain_small_dataset_with_tokenizer autotrain_compatible endpoints_compatible text-generation-inference region:us
---
base_model: OmarHaroon01/t5_pretrain_small_dataset_with_tokenizer
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5_pretrain_small_dataset_with_tokenizer-samsum
  results: []
---

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# t5_pretrain_small_dataset_with_tokenizer-samsum

This model is a fine-tuned version of [OmarHaroon01/t5_pretrain_small_dataset_with_tokenizer](https://huggingface.co/OmarHaroon01/t5_pretrain_small_dataset_with_tokenizer) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4729
- Rouge1: 17.7386
- Rouge2: 3.11
- Rougel: 15.15
- Rougelsum: 16.573
- Gen Len: 16.3223

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 5.2214        | 1.0   | 1842 | 4.9667          | 14.3736 | 2.0911 | 12.3289 | 13.1814   | 15.9072 |
| 4.8527        | 2.0   | 3684 | 4.7374          | 15.0596 | 2.1818 | 12.5768 | 13.9161   | 17.0855 |
| 4.6285        | 3.0   | 5526 | 4.5960          | 16.3996 | 2.7141 | 14.0638 | 15.2855   | 16.4164 |
| 4.5128        | 4.0   | 7368 | 4.5073          | 17.4296 | 2.9248 | 14.7579 | 16.163    | 16.1685 |
| 4.424         | 5.0   | 9210 | 4.4729          | 17.7386 | 3.11   | 15.15   | 16.573    | 16.3223 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
