---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
model-index:
- name: ALL_mt5-base_15_spider
  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. -->

# ALL_mt5-base_15_spider

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7395
- Rouge2 Precision: 0.397
- Rouge2 Recall: 0.2374
- Rouge2 Fmeasure: 0.2735

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 7.6173        | 1.0   | 875   | 1.8215          | 0.3407           | 0.1794        | 0.2153          |
| 0.2111        | 2.0   | 1750  | 3.9411          | 0.3658           | 0.2228        | 0.2572          |
| 0.1338        | 3.0   | 2625  | 4.4136          | 0.3594           | 0.2184        | 0.2522          |
| 0.105         | 4.0   | 3500  | 4.4853          | 0.3795           | 0.2302        | 0.264           |
| 0.0923        | 5.0   | 4375  | 4.4951          | 0.3768           | 0.227         | 0.2606          |
| 0.0771        | 6.0   | 5250  | 4.5377          | 0.3772           | 0.229         | 0.263           |
| 0.0666        | 7.0   | 6125  | 4.5821          | 0.3995           | 0.2366        | 0.2732          |
| 0.0581        | 8.0   | 7000  | 4.7276          | 0.4024           | 0.2375        | 0.2749          |
| 0.0541        | 9.0   | 7875  | 4.6743          | 0.4072           | 0.2412        | 0.2789          |
| 0.0495        | 10.0  | 8750  | 4.5628          | 0.3983           | 0.2387        | 0.2748          |
| 0.0455        | 11.0  | 9625  | 4.5861          | 0.3942           | 0.2363        | 0.2722          |
| 0.0428        | 12.0  | 10500 | 4.7071          | 0.3867           | 0.2364        | 0.2712          |
| 0.0417        | 13.0  | 11375 | 4.7196          | 0.3971           | 0.2375        | 0.2739          |
| 0.0396        | 14.0  | 12250 | 4.7196          | 0.3956           | 0.2371        | 0.2727          |
| 0.0381        | 15.0  | 13125 | 4.7395          | 0.397            | 0.2374        | 0.2735          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0