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---
license: apache-2.0
base_model: google/umt5-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: kp-umt5-base
  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. -->

# kp-umt5-base

This model is a fine-tuned version of [google/umt5-base](https://huggingface.co/google/umt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5488
- Bleu: 9.2954
- Gen Len: 18.0013

## 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: 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: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 4.1202        | 0.03  | 1000  | 2.9777          | 2.8238 | 18.173  |
| 3.5142        | 0.05  | 2000  | 2.5373          | 4.457  | 18.0813 |
| 3.1913        | 0.08  | 3000  | 2.3418          | 5.029  | 18.019  |
| 3.0343        | 0.11  | 4000  | 2.2078          | 5.5467 | 18.163  |
| 2.9           | 0.14  | 5000  | 2.1214          | 5.9178 | 18.14   |
| 2.7425        | 0.16  | 6000  | 2.0479          | 6.1516 | 18.0753 |
| 2.6798        | 0.19  | 7000  | 1.9939          | 6.4309 | 18.1157 |
| 2.6029        | 0.22  | 8000  | 1.9368          | 6.7683 | 18.1533 |
| 2.5378        | 0.24  | 9000  | 1.8959          | 6.9762 | 18.1603 |
| 2.5132        | 0.27  | 10000 | 1.8602          | 7.3219 | 18.2093 |
| 2.4394        | 0.3   | 11000 | 1.8264          | 7.3572 | 18.158  |
| 2.4158        | 0.33  | 12000 | 1.7959          | 7.5914 | 18.1257 |
| 2.3339        | 0.35  | 13000 | 1.7696          | 7.6829 | 18.077  |
| 2.3397        | 0.38  | 14000 | 1.7440          | 7.87   | 18.0993 |
| 2.293         | 0.41  | 15000 | 1.7219          | 8.1915 | 18.1303 |
| 2.2591        | 0.44  | 16000 | 1.7057          | 8.2801 | 18.0963 |
| 2.274         | 0.46  | 17000 | 1.6874          | 8.4263 | 18.0953 |
| 2.2387        | 0.49  | 18000 | 1.6709          | 8.5568 | 18.0837 |
| 2.2176        | 0.52  | 19000 | 1.6527          | 8.6313 | 18.0767 |
| 2.1742        | 0.54  | 20000 | 1.6414          | 8.718  | 18.0613 |
| 2.2095        | 0.57  | 21000 | 1.6260          | 8.8699 | 18.044  |
| 2.1936        | 0.6   | 22000 | 1.6154          | 8.8912 | 18.0573 |
| 2.0923        | 0.63  | 23000 | 1.6119          | 8.9109 | 18.091  |
| 2.1835        | 0.65  | 24000 | 1.6015          | 8.9474 | 18.0533 |
| 2.1374        | 0.68  | 25000 | 1.5962          | 9.0021 | 18.064  |
| 2.1286        | 0.71  | 26000 | 1.5816          | 9.0722 | 18.06   |
| 2.0589        | 0.73  | 27000 | 1.5787          | 9.1697 | 18.0667 |
| 2.0535        | 0.76  | 28000 | 1.5755          | 9.2336 | 18.05   |
| 2.1078        | 0.79  | 29000 | 1.5697          | 9.1774 | 18.0537 |
| 2.05          | 0.82  | 30000 | 1.5635          | 9.2354 | 18.0347 |
| 2.0517        | 0.84  | 31000 | 1.5593          | 9.2574 | 18.0013 |
| 2.0802        | 0.87  | 32000 | 1.5549          | 9.2727 | 18.0113 |
| 2.0137        | 0.9   | 33000 | 1.5540          | 9.2265 | 18.0007 |
| 2.069         | 0.92  | 34000 | 1.5497          | 9.3092 | 18.019  |
| 2.0969        | 0.95  | 35000 | 1.5498          | 9.2936 | 18.0113 |
| 2.0911        | 0.98  | 36000 | 1.5488          | 9.2954 | 18.0013 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1