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---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
datasets:
- opus_infopankki
metrics:
- bleu
model-index:
- name: mt5-small-parsinlu-opus-translation_fa_en-finetuned-fa-to-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: opus_infopankki
type: opus_infopankki
args: en-fa
metrics:
- name: Bleu
type: bleu
value: 9.5106
---
<!-- 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. -->
# mt5-small-parsinlu-opus-translation_fa_en-finetuned-fa-to-en
This model is a fine-tuned version of [persiannlp/mt5-small-parsinlu-opus-translation_fa_en](https://huggingface.co/persiannlp/mt5-small-parsinlu-opus-translation_fa_en) on the opus_infopankki dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5449
- Bleu: 9.5106
- Gen Len: 13.6434
## 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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log | 1.0 | 151 | 3.1656 | 7.194 | 14.1885 |
| No log | 2.0 | 302 | 3.0419 | 7.7031 | 14.1005 |
| No log | 3.0 | 453 | 2.9549 | 8.1502 | 13.9834 |
| 3.5336 | 4.0 | 604 | 2.8857 | 8.4488 | 13.9251 |
| 3.5336 | 5.0 | 755 | 2.8297 | 8.6606 | 13.786 |
| 3.5336 | 6.0 | 906 | 2.7808 | 8.8217 | 13.7983 |
| 3.2511 | 7.0 | 1057 | 2.7386 | 8.9221 | 13.7518 |
| 3.2511 | 8.0 | 1208 | 2.7006 | 9.1988 | 13.7159 |
| 3.2511 | 9.0 | 1359 | 2.6678 | 9.2751 | 13.676 |
| 3.1055 | 10.0 | 1510 | 2.6387 | 9.4142 | 13.6648 |
| 3.1055 | 11.0 | 1661 | 2.6154 | 9.5726 | 13.6841 |
| 3.1055 | 12.0 | 1812 | 2.5945 | 9.6571 | 13.6546 |
| 3.1055 | 13.0 | 1963 | 2.5813 | 9.8303 | 13.6571 |
| 3.0199 | 14.0 | 2114 | 2.5709 | 9.6726 | 13.5855 |
| 3.0199 | 15.0 | 2265 | 2.5619 | 9.632 | 13.6125 |
| 3.0199 | 16.0 | 2416 | 2.5563 | 9.5773 | 13.6256 |
| 2.9862 | 17.0 | 2567 | 2.5538 | 9.5425 | 13.6366 |
| 2.9862 | 18.0 | 2718 | 2.5515 | 9.5359 | 13.6326 |
| 2.9862 | 19.0 | 2869 | 2.5495 | 9.5544 | 13.642 |
| 2.9859 | 20.0 | 3020 | 2.5478 | 9.5183 | 13.6374 |
| 2.9859 | 21.0 | 3171 | 2.5466 | 9.5387 | 13.632 |
| 2.9859 | 22.0 | 3322 | 2.5458 | 9.5183 | 13.6355 |
| 2.9859 | 23.0 | 3473 | 2.5451 | 9.5019 | 13.6376 |
| 2.9731 | 24.0 | 3624 | 2.5449 | 9.5004 | 13.6405 |
| 2.9731 | 25.0 | 3775 | 2.5449 | 9.5106 | 13.6434 |
| 2.9731 | 26.0 | 3926 | 2.5449 | 9.5106 | 13.6434 |
| 2.9671 | 27.0 | 4077 | 2.5449 | 9.5106 | 13.6434 |
| 2.9671 | 28.0 | 4228 | 2.5449 | 9.5106 | 13.6434 |
| 2.9671 | 29.0 | 4379 | 2.5449 | 9.5106 | 13.6434 |
| 2.97 | 30.0 | 4530 | 2.5449 | 9.5106 | 13.6434 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.7.1+cu110
- Datasets 2.2.2
- Tokenizers 0.12.1
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