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# 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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["pn_summary"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-persian-dataset", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "pn_summary", "type": "pn_summary", "config": "1.0.0", "split": "validation", "args": "1.0.0"}, "metrics": [{"type": "rouge", "value": 28.6676, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard mt5 text2text-generation generated_from_trainer dataset:pn_summary license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #dataset-pn_summary #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mt5-small-persian-dataset
=========================


This model is a fine-tuned version of 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



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #dataset-pn_summary #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### 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 ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #dataset-pn_summary #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### 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### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2