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_t5_f3_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_t5_f3_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: 0.0674
- Rouge1: 79.2211
- Rouge2: 73.7497
- Rougel: 79.2024
- Rougelsum: 79.199
- Gen Len: 12.0360

## 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   | 271  | 0.1073          | 74.7884 | 68.0509 | 74.791  | 74.7345   | 12.0097 |
| 0.4704        | 2.0   | 542  | 0.0746          | 77.5977 | 71.7478 | 77.6371 | 77.6192   | 12.0332 |
| 0.4704        | 3.0   | 813  | 0.0710          | 78.5683 | 73.0397 | 78.5601 | 78.5631   | 12.0180 |
| 0.0852        | 4.0   | 1084 | 0.0671          | 78.7386 | 73.1012 | 78.7286 | 78.7115   | 12.0277 |
| 0.0852        | 5.0   | 1355 | 0.0674          | 79.2211 | 73.7497 | 79.2024 | 79.199    | 12.0360 |


### Framework versions

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