---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- rouge
base_model: google-t5/t5-base
model-index:
- name: t5base-ILC
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5base-ILC

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on [ILC dataset](https://huggingface.co/datasets/d0r1h/ILC).
It achieves the following results on the evaluation set:
- Loss: 3.1984
- Rouge1: 8.381
- Rouge2: 3.916
- Rougel: 7.0243
- Rougelsum: 7.8617
- Gen Len: 18.9833

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 10.5936       | 0.49  | 500  | 4.4985          | 7.204  | 2.8587 | 5.9813 | 6.774     | 18.9665 |
| 3.9459        | 0.97  | 1000 | 3.1984          | 8.381  | 3.916  | 7.0243 | 7.8617    | 18.9833 |


### Framework versions

- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2