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_f0_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_f0_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: 0.0532
- Rouge1: 84.7093
- Rouge2: 80.7973
- Rougel: 84.7729
- Rougelsum: 84.7122
- Gen Len: 12.1441

## 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  | 0.0737          | 82.0209 | 76.901  | 82.1038 | 82.0496   | 12.0960 |
| 0.403         | 2.0   | 532  | 0.0612          | 83.1998 | 78.7278 | 83.2379 | 83.2163   | 12.1582 |
| 0.403         | 3.0   | 798  | 0.0588          | 84.7251 | 80.7619 | 84.8122 | 84.7804   | 12.1003 |
| 0.0755        | 4.0   | 1064 | 0.0540          | 84.3926 | 80.3941 | 84.4621 | 84.4156   | 12.1455 |
| 0.0755        | 5.0   | 1330 | 0.0532          | 84.7093 | 80.7973 | 84.7729 | 84.7122   | 12.1441 |


### Framework versions

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