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# mt5-small-text-sum-7

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3801
- Rouge1: 20.58
- Rouge2: 6.51
- Rougel: 20.26

## 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: 0.0001
- train_batch_size: 13
- eval_batch_size: 13
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 4.4436        | 2.09  | 500  | 2.5528          | 17.73  | 5.9    | 17.55  |
| 3.0439        | 4.18  | 1000 | 2.4974          | 18.76  | 5.73   | 18.64  |
| 2.822         | 6.28  | 1500 | 2.4043          | 17.82  | 5.09   | 17.68  |
| 2.6799        | 8.37  | 2000 | 2.3938          | 18.9   | 5.73   | 18.62  |
| 2.5687        | 10.46 | 2500 | 2.3617          | 19.0   | 5.76   | 18.73  |
| 2.4701        | 12.55 | 3000 | 2.3455          | 19.82  | 6.14   | 19.54  |
| 2.3917        | 14.64 | 3500 | 2.3801          | 20.58  | 6.51   | 20.26  |
| 2.3427        | 16.74 | 4000 | 2.3407          | 19.52  | 6.49   | 19.23  |
| 2.2811        | 18.83 | 4500 | 2.3544          | 18.82  | 5.75   | 18.43  |
| 2.2347        | 20.92 | 5000 | 2.3503          | 20.17  | 6.08   | 19.76  |
| 2.1884        | 23.01 | 5500 | 2.3586          | 20.25  | 6.06   | 19.9   |
| 2.1414        | 25.1  | 6000 | 2.3507          | 19.94  | 6.31   | 19.61  |


### Framework versions

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

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-text-sum-7", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mt5-small-text-sum-7
====================


This model is a fine-tuned version of google/mt5-small on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3801
* Rouge1: 20.58
* Rouge2: 6.51
* Rougel: 20.26


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: 0.0001
* train\_batch\_size: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40


### 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: 0.0001
* train\_batch\_size: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40 ### 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 #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40 ### 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 #summarization #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 13
* eval\_batch\_size: 13
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 40### Training results### Framework versions


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