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_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_t4_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: 0.0671
- Rouge1: 83.3724
- Rouge2: 78.8702
- Rougel: 83.3375
- Rougelsum: 83.3498
- Gen Len: 12.1455

## 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  | 0.0929          | 79.8647 | 74.2176 | 79.8122 | 79.8407   | 12.0932 |
| 0.4053        | 2.0   | 532  | 0.0703          | 82.3346 | 77.6611 | 82.3273 | 82.3379   | 12.1554 |
| 0.4053        | 3.0   | 798  | 0.0653          | 82.7695 | 78.1829 | 82.7524 | 82.7387   | 12.1624 |
| 0.0748        | 4.0   | 1064 | 0.0653          | 83.5716 | 79.168  | 83.5269 | 83.5043   | 12.1568 |
| 0.0748        | 5.0   | 1330 | 0.0671          | 83.3724 | 78.8702 | 83.3375 | 83.3498   | 12.1455 |


### Framework versions

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