---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: qaharoldv1-expediaexp1
  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. -->

# qaharoldv1-expediaexp1

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4137
- Rouge1: 0.8305
- Rouge2: 0.6845
- Rougel: 0.8105
- Gen Len: 71.1

## 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: 0.0004
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
| No log        | 0.48  | 100  | 0.5590          | 0.7684 | 0.5676 | 0.7355 | 71.1    |
| No log        | 0.95  | 200  | 0.4939          | 0.7921 | 0.6073 | 0.7614 | 71.1    |
| No log        | 1.43  | 300  | 0.4513          | 0.8005 | 0.6189 | 0.7711 | 71.1    |
| No log        | 1.9   | 400  | 0.4188          | 0.8075 | 0.6419 | 0.7838 | 71.1    |
| No log        | 2.38  | 500  | 0.4230          | 0.8123 | 0.6549 | 0.7912 | 71.1    |
| No log        | 2.86  | 600  | 0.4149          | 0.8186 | 0.6678 | 0.8013 | 71.1    |
| No log        | 3.33  | 700  | 0.4090          | 0.8155 | 0.6574 | 0.796  | 71.1    |
| No log        | 3.81  | 800  | 0.4066          | 0.8238 | 0.6643 | 0.8009 | 71.1    |
| No log        | 4.29  | 900  | 0.4030          | 0.8253 | 0.668  | 0.8024 | 71.1    |
| No log        | 4.76  | 1000 | 0.4037          | 0.8211 | 0.6729 | 0.8034 | 71.1    |
| No log        | 5.24  | 1100 | 0.4066          | 0.8199 | 0.6662 | 0.8003 | 71.1    |
| No log        | 5.71  | 1200 | 0.4065          | 0.8249 | 0.666  | 0.8024 | 71.1    |
| No log        | 6.19  | 1300 | 0.4216          | 0.828  | 0.6858 | 0.8105 | 71.1    |
| No log        | 6.67  | 1400 | 0.3972          | 0.8318 | 0.6869 | 0.8129 | 71.1    |
| No log        | 7.14  | 1500 | 0.4047          | 0.8297 | 0.6839 | 0.8111 | 71.1    |
| No log        | 7.62  | 1600 | 0.4083          | 0.8294 | 0.6859 | 0.811  | 71.1    |
| No log        | 8.1   | 1700 | 0.4071          | 0.8305 | 0.6831 | 0.8094 | 71.1    |
| No log        | 8.57  | 1800 | 0.4080          | 0.8307 | 0.6868 | 0.8115 | 71.1    |
| No log        | 9.05  | 1900 | 0.4098          | 0.831  | 0.6864 | 0.8111 | 71.1    |
| No log        | 9.52  | 2000 | 0.4145          | 0.8299 | 0.6838 | 0.8099 | 71.1    |
| No log        | 10.0  | 2100 | 0.4137          | 0.8305 | 0.6845 | 0.8105 | 71.1    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.2.2+cu121
- Datasets 2.2.1
- Tokenizers 0.15.2