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_t3_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_t3_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: 0.0589
- Rouge1: 83.8592
- Rouge2: 79.6964
- Rougel: 83.8653
- Rougelsum: 83.8907
- Gen Len: 12.0564

## 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   | 259  | 0.0870          | 79.2884 | 73.7674 | 79.2737 | 79.2658   | 12.0029 |
| 0.4029        | 2.0   | 518  | 0.0723          | 82.4137 | 77.8327 | 82.4253 | 82.4151   | 12.0202 |
| 0.4029        | 3.0   | 777  | 0.0579          | 83.4685 | 79.1137 | 83.4737 | 83.4759   | 12.0723 |
| 0.0721        | 4.0   | 1036 | 0.0561          | 83.5346 | 79.1485 | 83.5099 | 83.5342   | 12.0650 |
| 0.0721        | 5.0   | 1295 | 0.0589          | 83.8592 | 79.6964 | 83.8653 | 83.8907   | 12.0564 |


### Framework versions

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