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# mt5-base-gecfirst-e8-b16

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3009
- Rouge1: 63.8499
- Rouge2: 56.2662
- Rougel: 63.73
- Rougelsum: 63.6591
- Gen Len: 18.7736

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.409         | 0.25  | 74   | 0.6899          | 58.0459 | 46.7233 | 57.9944 | 57.9576   | 18.7669 |
| 1.0497        | 0.5   | 148  | 0.4335          | 61.3353 | 51.8804 | 61.174  | 61.1541   | 18.7703 |
| 0.8355        | 0.75  | 222  | 0.3734          | 62.5279 | 54.5952 | 62.4436 | 62.4377   | 18.7720 |
| 0.7339        | 1.0   | 296  | 0.3814          | 62.8071 | 54.8468 | 62.7075 | 62.6933   | 18.7770 |
| 0.5946        | 1.25  | 370  | 0.3418          | 63.1523 | 55.3752 | 62.9987 | 62.9879   | 18.7770 |
| 0.5746        | 1.49  | 444  | 0.3234          | 62.9253 | 55.1955 | 62.821  | 62.7592   | 18.7905 |
| 0.5278        | 1.74  | 518  | 0.3252          | 63.3056 | 55.6505 | 63.1271 | 63.0661   | 18.7804 |
| 0.4886        | 1.99  | 592  | 0.3265          | 63.1652 | 55.0909 | 62.979  | 62.9613   | 18.7753 |
| 0.366         | 2.24  | 666  | 0.3126          | 63.8131 | 56.5685 | 63.7303 | 63.6682   | 18.7703 |
| 0.3553        | 2.49  | 740  | 0.3192          | 63.6195 | 55.9276 | 63.4796 | 63.4692   | 18.7703 |
| 0.3558        | 2.74  | 814  | 0.3009          | 63.8499 | 56.2662 | 63.73   | 63.6591   | 18.7736 |
| 0.353         | 2.99  | 888  | 0.3014          | 63.7417 | 56.241  | 63.6192 | 63.5985   | 18.7686 |
| 0.2398        | 3.24  | 962  | 0.3119          | 63.999  | 56.8854 | 63.88   | 63.8705   | 18.7804 |
| 0.2459        | 3.49  | 1036 | 0.3222          | 64.0299 | 56.5581 | 63.9247 | 63.8934   | 18.7686 |
| 0.2423        | 3.74  | 1110 | 0.3125          | 63.6601 | 56.1864 | 63.4956 | 63.4819   | 18.7686 |
| 0.243         | 3.99  | 1184 | 0.3174          | 63.6676 | 56.1724 | 63.5183 | 63.4947   | 18.7736 |
| 0.1696        | 4.24  | 1258 | 0.3353          | 63.9905 | 56.3781 | 63.7979 | 63.7802   | 18.7652 |
| 0.1643        | 4.48  | 1332 | 0.3386          | 64.0219 | 56.7311 | 63.8823 | 63.8654   | 18.7703 |
| 0.1728        | 4.73  | 1406 | 0.3306          | 64.0261 | 56.7331 | 63.8978 | 63.8731   | 18.7720 |
| 0.1657        | 4.98  | 1480 | 0.3269          | 63.9735 | 56.4556 | 63.8514 | 63.8168   | 18.7703 |
| 0.1186        | 5.23  | 1554 | 0.3390          | 63.9831 | 56.6624 | 63.8953 | 63.8717   | 18.7703 |
| 0.1129        | 5.48  | 1628 | 0.3521          | 63.8674 | 56.528  | 63.7626 | 63.7362   | 18.7770 |
| 0.1061        | 5.73  | 1702 | 0.3539          | 63.9886 | 56.5753 | 63.881  | 63.8615   | 18.7703 |
| 0.1179        | 5.98  | 1776 | 0.3490          | 63.9949 | 56.7369 | 63.8929 | 63.8516   | 18.7736 |
| 0.0793        | 6.23  | 1850 | 0.3704          | 64.1527 | 57.0111 | 64.0496 | 63.9953   | 18.7686 |
| 0.0779        | 6.48  | 1924 | 0.3723          | 64.1833 | 57.0654 | 64.0686 | 64.0317   | 18.7669 |
| 0.0827        | 6.73  | 1998 | 0.3663          | 64.2185 | 56.9382 | 64.1096 | 64.0743   | 18.7736 |
| 0.0807        | 6.98  | 2072 | 0.3691          | 64.2298 | 56.9752 | 64.0957 | 64.0777   | 18.7686 |
| 0.0633        | 7.23  | 2146 | 0.3865          | 64.4729 | 57.5503 | 64.3733 | 64.3509   | 18.7652 |
| 0.0603        | 7.47  | 2220 | 0.3919          | 64.3001 | 57.2684 | 64.1693 | 64.1391   | 18.7635 |
| 0.0565        | 7.72  | 2294 | 0.3946          | 64.4077 | 57.3413 | 64.2825 | 64.2491   | 18.7635 |
| 0.0583        | 7.97  | 2368 | 0.3923          | 64.4078 | 57.3672 | 64.2775 | 64.2367   | 18.7652 |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.11.0a0+b6df043
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-base-gecfirst-e8-b16", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

mt5-base-gecfirst-e8-b16
========================


This model is a fine-tuned version of google/mt5-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3009
* Rouge1: 63.8499
* Rouge2: 56.2662
* Rougel: 63.73
* Rougelsum: 63.6591
* Gen Len: 18.7736


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: 0.001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adafactor
* lr\_scheduler\_type: linear
* num\_epochs: 8


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.11.0a0+b6df043
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adafactor
* lr\_scheduler\_type: linear
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.11.0a0+b6df043
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #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: 0.001
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adafactor
* lr\_scheduler\_type: linear
* num\_epochs: 8 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.11.0a0+b6df043
* Datasets 2.12.0
* Tokenizers 0.13.3