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: test-dialogue-summarization-headers
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# test-dialogue-summarization-headers

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4536
- Rouge: {'rouge1': 44.8698, 'rouge2': 19.92, 'rougeL': 20.7147, 'rougeLsum': 20.7147}
- Bert Score: 0.8733
- Bleurt 20: -0.8548
- Gen Len: 15.305

## 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: 2e-05
- train_batch_size: 7
- eval_batch_size: 7
- 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 | Rouge                                                                           | Bert Score | Bleurt 20 | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------:|:----------:|:---------:|:-------:|
| 2.6545        | 1.0   | 186  | 2.5321          | {'rouge1': 45.8489, 'rouge2': 19.7993, 'rougeL': 20.5196, 'rougeLsum': 20.5196} | 0.8737     | -0.8571   | 15.16   |
| 2.6779        | 2.0   | 372  | 2.4884          | {'rouge1': 44.2284, 'rouge2': 19.6646, 'rougeL': 20.6804, 'rougeLsum': 20.6804} | 0.8737     | -0.8594   | 15.13   |
| 2.6701        | 3.0   | 558  | 2.4682          | {'rouge1': 44.6249, 'rouge2': 19.9539, 'rougeL': 20.6036, 'rougeLsum': 20.6036} | 0.8737     | -0.8576   | 15.25   |
| 2.597         | 4.0   | 744  | 2.4582          | {'rouge1': 45.0018, 'rouge2': 19.7794, 'rougeL': 20.647, 'rougeLsum': 20.647}   | 0.8739     | -0.8582   | 15.295  |
| 2.5861        | 5.0   | 930  | 2.4536          | {'rouge1': 44.8698, 'rouge2': 19.92, 'rougeL': 20.7147, 'rougeLsum': 20.7147}   | 0.8733     | -0.8548   | 15.305  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
