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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pn_summary
metrics:
- rouge
model-index:
- name: mt5-small-persian-dataset
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: pn_summary
type: pn_summary
config: 1.0.0
split: validation
args: 1.0.0
metrics:
- name: Rouge1
type: rouge
value: 28.6676
---
<!-- 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-persian-dataset
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the pn_summary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9495
- Rouge1: 28.6676
- Rouge2: 12.4796
- Rougel: 26.0552
- Rougelsum: 26.0624
## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 4.3518 | 1.0 | 1139 | 2.2437 | 24.8632 | 10.0197 | 22.5098 | 22.5578 |
| 2.8053 | 2.0 | 2278 | 2.1084 | 26.7746 | 11.2038 | 24.1918 | 24.1592 |
| 2.5852 | 3.0 | 3417 | 2.0525 | 27.3138 | 11.6092 | 24.795 | 24.765 |
| 2.4537 | 4.0 | 4556 | 2.0333 | 27.8395 | 11.92 | 25.1716 | 25.1786 |
| 2.3629 | 5.0 | 5695 | 1.9973 | 28.4229 | 12.2162 | 25.7546 | 25.7399 |
| 2.3007 | 6.0 | 6834 | 1.9752 | 28.259 | 12.3229 | 25.6448 | 25.6348 |
| 2.2527 | 7.0 | 7973 | 1.9605 | 28.7359 | 12.608 | 26.0384 | 26.0478 |
| 2.2227 | 8.0 | 9112 | 1.9571 | 28.5958 | 12.4125 | 25.9516 | 25.9815 |
| 2.1983 | 9.0 | 10251 | 1.9557 | 28.5015 | 12.4138 | 25.8887 | 25.8967 |
| 2.1769 | 10.0 | 11390 | 1.9495 | 28.6676 | 12.4796 | 26.0552 | 26.0624 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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