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_f1_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_f1_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: 0.0647
- Rouge1: 79.2006
- Rouge2: 73.7804
- Rougel: 79.2274
- Rougelsum: 79.2405
- Gen Len: 12.0471

## 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  | 0.0993          | 76.0054 | 69.0068 | 76.0105 | 75.9722   | 12.0014 |
| 0.4749        | 2.0   | 542  | 0.0693          | 78.2033 | 72.3784 | 78.2208 | 78.1724   | 12.0540 |
| 0.4749        | 3.0   | 813  | 0.0660          | 79.4313 | 73.9365 | 79.4865 | 79.4338   | 12.0429 |
| 0.0883        | 4.0   | 1084 | 0.0644          | 79.2898 | 73.9021 | 79.3393 | 79.3354   | 12.0568 |
| 0.0883        | 5.0   | 1355 | 0.0647          | 79.2006 | 73.7804 | 79.2274 | 79.2405   | 12.0471 |


### Framework versions

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