transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-base license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: test-dialogue-summarization
  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

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0710
- Rouge: {'rouge1': 46.5916, 'rouge2': 21.9208, 'rougeL': 22.0124, 'rougeLsum': 22.0124}
- Bert Score: 0.8784
- Bleurt 20: -0.7903
- Gen Len: 15.58

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------:|:----------:|:---------:|:-------:|
| 2.5288        | 1.0   | 186  | 2.1809          | {'rouge1': 48.087, 'rouge2': 21.7173, 'rougeL': 21.5447, 'rougeLsum': 21.5447}  | 0.877      | -0.8143   | 15.63   |
| 2.3277        | 2.0   | 372  | 2.1230          | {'rouge1': 47.3856, 'rouge2': 21.3069, 'rougeL': 21.6399, 'rougeLsum': 21.6399} | 0.8788     | -0.786    | 15.54   |
| 2.2381        | 3.0   | 558  | 2.0912          | {'rouge1': 45.9843, 'rouge2': 21.1854, 'rougeL': 21.4006, 'rougeLsum': 21.4006} | 0.8776     | -0.817    | 15.235  |
| 2.2123        | 4.0   | 744  | 2.0761          | {'rouge1': 46.5269, 'rouge2': 21.7291, 'rougeL': 21.8936, 'rougeLsum': 21.8936} | 0.8785     | -0.7809   | 15.515  |
| 2.2443        | 5.0   | 930  | 2.0710          | {'rouge1': 46.5916, 'rouge2': 21.9208, 'rougeL': 22.0124, 'rougeLsum': 22.0124} | 0.8784     | -0.7903   | 15.58   |


### Framework versions

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