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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
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