transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-small base_model:finetune:google/flan-t5-small license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: google/flan-t5-small
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
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-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3848
- Rouge: {'rouge1': 45.6704, 'rouge2': 21.245, 'rougeL': 20.2411, 'rougeLsum': 20.2411}
- Bert Score: 0.8718
- Bleurt 20: -0.8946
- Gen Len: 14.99

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------:|:----------:|:---------:|:-------:|
| 2.2971        | 1.0   | 186  | 2.4618          | {'rouge1': 46.8614, 'rouge2': 21.2026, 'rougeL': 20.3766, 'rougeLsum': 20.3766} | 0.8719     | -0.8804   | 15.38   |
| 2.5384        | 2.0   | 372  | 2.4062          | {'rouge1': 46.4924, 'rouge2': 21.6223, 'rougeL': 20.304, 'rougeLsum': 20.304}   | 0.8724     | -0.8819   | 15.145  |
| 2.5224        | 3.0   | 558  | 2.3936          | {'rouge1': 46.0775, 'rouge2': 21.2642, 'rougeL': 20.3148, 'rougeLsum': 20.3148} | 0.871      | -0.8905   | 15.345  |
| 2.4661        | 4.0   | 744  | 2.3867          | {'rouge1': 45.6718, 'rouge2': 21.122, 'rougeL': 20.2877, 'rougeLsum': 20.2877}  | 0.8719     | -0.8887   | 14.975  |
| 2.4426        | 5.0   | 930  | 2.3848          | {'rouge1': 45.6704, 'rouge2': 21.245, 'rougeL': 20.2411, 'rougeLsum': 20.2411}  | 0.8718     | -0.8946   | 14.99   |


### Framework versions

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