transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: flan-t5-small-asap_t4_f4_prompt_adherence
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# flan-t5-small-asap_t4_f4_prompt_adherence

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0597
- Rouge1: 83.822
- Rouge2: 79.5644
- Rougel: 83.8414
- Rougelsum: 83.8601
- Gen Len: 12.1384

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 266  | 0.0783          | 82.3137 | 77.2617 | 82.3362 | 82.3581   | 12.1836 |
| 0.4094        | 2.0   | 532  | 0.0676          | 82.9368 | 78.4362 | 82.962  | 82.9633   | 12.1356 |
| 0.4094        | 3.0   | 798  | 0.0571          | 84.7957 | 80.9486 | 84.8665 | 84.8224   | 12.1963 |
| 0.0756        | 4.0   | 1064 | 0.0577          | 84.5562 | 80.4996 | 84.5733 | 84.5457   | 12.1667 |
| 0.0756        | 5.0   | 1330 | 0.0597          | 83.822  | 79.5644 | 83.8414 | 83.8601   | 12.1384 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
