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# mt5-small-finetuned-1feb-2

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: 2.3856
- Rouge1: 8.74
- Rouge2: 2.66
- Rougel: 8.58
- Rougelsum: 8.6

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.3153        | 1.0   | 311  | 2.6946          | 7.56   | 2.04   | 7.55   | 7.46      |
| 3.3159        | 2.0   | 622  | 2.5923          | 8.07   | 2.28   | 8.05   | 8.02      |
| 3.092         | 3.0   | 933  | 2.5342          | 7.83   | 2.01   | 7.81   | 7.76      |
| 2.9676        | 4.0   | 1244 | 2.4982          | 8.45   | 2.49   | 8.37   | 8.39      |
| 2.862         | 5.0   | 1555 | 2.4627          | 8.3    | 2.5    | 8.26   | 8.27      |
| 2.7891        | 6.0   | 1866 | 2.4366          | 8.67   | 2.81   | 8.53   | 8.55      |
| 2.7391        | 7.0   | 2177 | 2.4215          | 8.51   | 2.54   | 8.45   | 8.42      |
| 2.6887        | 8.0   | 2488 | 2.4277          | 8.71   | 2.53   | 8.56   | 8.54      |
| 2.6392        | 9.0   | 2799 | 2.3939          | 8.49   | 2.53   | 8.4    | 8.4       |
| 2.6139        | 10.0  | 3110 | 2.4015          | 9.28   | 2.85   | 9.14   | 9.19      |
| 2.5727        | 11.0  | 3421 | 2.3956          | 9.24   | 2.9    | 9.08   | 9.09      |
| 2.5595        | 12.0  | 3732 | 2.3856          | 8.45   | 2.59   | 8.31   | 8.35      |
| 2.5471        | 13.0  | 4043 | 2.3891          | 8.64   | 2.79   | 8.53   | 8.52      |
| 2.5231        | 14.0  | 4354 | 2.3870          | 8.78   | 2.79   | 8.64   | 8.6       |
| 2.5024        | 15.0  | 4665 | 2.3856          | 8.74   | 2.66   | 8.58   | 8.6       |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["summarization", "generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-small-finetuned-1feb-2", "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-1feb-2
==========================


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: 2.3856
* Rouge1: 8.74
* Rouge2: 2.66
* Rougel: 8.58
* Rougelsum: 8.6


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: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* 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: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15 ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* 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: 10
* eval\_batch\_size: 10
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 15### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2