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# mt5-small-finetuned-26feb-1

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: 2.4486
- Rouge1: 20.86
- Rouge2: 6.45
- Rougel: 20.49

## 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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|
| 5.4839        | 1.93  | 500   | 2.5990          | 16.14  | 5.18   | 15.98  |
| 3.1051        | 3.86  | 1000  | 2.4754          | 18.71  | 5.68   | 18.41  |
| 2.8659        | 5.79  | 1500  | 2.4006          | 18.22  | 5.54   | 18.06  |
| 2.71          | 7.72  | 2000  | 2.3848          | 19.91  | 6.0    | 19.65  |
| 2.5845        | 9.65  | 2500  | 2.3956          | 18.72  | 5.72   | 18.4   |
| 2.4895        | 11.58 | 3000  | 2.3719          | 19.9   | 6.1    | 19.54  |
| 2.402         | 13.51 | 3500  | 2.3691          | 19.86  | 5.79   | 19.51  |
| 2.3089        | 15.44 | 4000  | 2.3747          | 20.22  | 6.74   | 19.88  |
| 2.2681        | 17.37 | 4500  | 2.3754          | 19.44  | 5.53   | 19.03  |
| 2.1927        | 19.31 | 5000  | 2.3419          | 20.02  | 5.91   | 19.69  |
| 2.1278        | 21.24 | 5500  | 2.3496          | 20.26  | 6.21   | 19.79  |
| 2.0928        | 23.17 | 6000  | 2.3756          | 19.9   | 6.04   | 19.48  |
| 2.0658        | 25.1  | 6500  | 2.3615          | 19.61  | 6.04   | 19.28  |
| 2.0063        | 27.03 | 7000  | 2.3516          | 20.38  | 6.52   | 20.14  |
| 1.9581        | 28.96 | 7500  | 2.3743          | 20.61  | 6.26   | 20.24  |
| 1.941         | 30.89 | 8000  | 2.3726          | 19.73  | 5.8    | 19.31  |
| 1.9172        | 32.82 | 8500  | 2.3891          | 19.73  | 5.98   | 19.51  |
| 1.8764        | 34.75 | 9000  | 2.3782          | 20.1   | 6.15   | 19.74  |
| 1.8453        | 36.68 | 9500  | 2.3851          | 19.96  | 6.0    | 19.61  |
| 1.845         | 38.61 | 10000 | 2.4046          | 20.66  | 6.32   | 20.24  |
| 1.7919        | 40.54 | 10500 | 2.4169          | 20.65  | 6.25   | 20.38  |
| 1.7945        | 42.47 | 11000 | 2.4206          | 20.68  | 5.74   | 20.37  |
| 1.7689        | 44.4  | 11500 | 2.4246          | 20.69  | 6.09   | 20.4   |
| 1.7215        | 46.33 | 12000 | 2.4237          | 20.49  | 6.43   | 20.21  |
| 1.7306        | 48.26 | 12500 | 2.4217          | 20.55  | 6.49   | 20.18  |
| 1.7035        | 50.19 | 13000 | 2.4389          | 20.81  | 6.55   | 20.48  |
| 1.6934        | 52.12 | 13500 | 2.4377          | 20.75  | 6.85   | 20.35  |
| 1.7           | 54.05 | 14000 | 2.4486          | 20.86  | 6.45   | 20.49  |
| 1.6909        | 55.98 | 14500 | 2.4451          | 20.5   | 6.55   | 20.12  |
| 1.6804        | 57.92 | 15000 | 2.4457          | 20.21  | 6.5    | 19.84  |
| 1.6693        | 59.85 | 15500 | 2.4473          | 20.35  | 6.6    | 19.96  |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-26feb-1", "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-finetuned-26feb-1
===========================


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: 2.4486
* Rouge1: 20.86
* Rouge2: 6.45
* Rougel: 20.49


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: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60


### Training results



### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* 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: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60 ### Training results ### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* 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: 12
* eval\_batch\_size: 12
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 60### Training results### Framework versions


* Transformers 4.26.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.0
* Tokenizers 0.13.2