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# mt5-large-gecfirst-e8-b16

This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2672
- Rouge1: 64.1391
- Rouge2: 56.9117
- Rougel: 64.0719
- Rougelsum: 64.1665
- Gen Len: 18.7753

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8204        | 0.25  | 74   | 0.4021          | 61.4087 | 52.3887 | 61.2674 | 61.3674   | 18.7804 |
| 0.7246        | 0.5   | 148  | 0.3252          | 63.347  | 55.3862 | 63.1874 | 63.2961   | 18.7652 |
| 0.6142        | 0.75  | 222  | 0.3028          | 63.725  | 56.2856 | 63.5597 | 63.6491   | 18.7838 |
| 0.5472        | 1.0   | 296  | 0.2919          | 63.8647 | 56.6097 | 63.7525 | 63.8544   | 18.7973 |
| 0.3687        | 1.25  | 370  | 0.2777          | 64.0686 | 56.686  | 63.883  | 63.9804   | 18.7703 |
| 0.3907        | 1.49  | 444  | 0.2870          | 64.0517 | 56.6668 | 63.9062 | 64.0017   | 18.7838 |
| 0.3466        | 1.74  | 518  | 0.2726          | 64.2559 | 57.4463 | 64.1045 | 64.2199   | 18.7770 |
| 0.3341        | 1.99  | 592  | 0.2672          | 64.1391 | 56.9117 | 64.0719 | 64.1665   | 18.7753 |
| 0.2036        | 2.24  | 666  | 0.2834          | 64.5476 | 57.8246 | 64.3771 | 64.5255   | 18.7804 |
| 0.2091        | 2.49  | 740  | 0.2897          | 64.1422 | 56.9715 | 64.0481 | 64.1689   | 18.7432 |
| 0.2002        | 2.74  | 814  | 0.2703          | 64.6648 | 57.707  | 64.4805 | 64.5948   | 18.7804 |
| 0.204         | 2.99  | 888  | 0.2824          | 64.0966 | 56.9705 | 63.9888 | 64.073    | 18.7551 |
| 0.1185        | 3.24  | 962  | 0.3022          | 64.4346 | 57.6011 | 64.3542 | 64.4615   | 18.7939 |
| 0.117         | 3.49  | 1036 | 0.2870          | 64.455  | 57.3607 | 64.2925 | 64.3963   | 18.7669 |
| 0.1135        | 3.74  | 1110 | 0.2890          | 64.7671 | 58.0409 | 64.5938 | 64.6987   | 18.7669 |
| 0.1175        | 3.99  | 1184 | 0.2977          | 64.8082 | 58.0379 | 64.6993 | 64.7849   | 18.7652 |
| 0.0726        | 4.24  | 1258 | 0.3135          | 64.5297 | 57.6752 | 64.4134 | 64.5109   | 18.7736 |
| 0.0654        | 4.48  | 1332 | 0.3298          | 64.5051 | 57.6982 | 64.3561 | 64.4885   | 18.7787 |
| 0.0719        | 4.73  | 1406 | 0.3139          | 64.8793 | 58.1936 | 64.749  | 64.8532   | 18.7720 |
| 0.0665        | 4.98  | 1480 | 0.3174          | 64.9015 | 58.1975 | 64.786  | 64.907    | 18.7703 |
| 0.0452        | 5.23  | 1554 | 0.3272          | 64.5715 | 58.067  | 64.4336 | 64.5425   | 18.7889 |
| 0.0395        | 5.48  | 1628 | 0.3337          | 64.7712 | 58.1058 | 64.6351 | 64.7423   | 18.7703 |
| 0.0367        | 5.73  | 1702 | 0.3422          | 64.9298 | 58.4592 | 64.8188 | 64.8927   | 18.7787 |
| 0.0393        | 5.98  | 1776 | 0.3394          | 64.8953 | 58.162  | 64.7892 | 64.8822   | 18.7787 |
| 0.0247        | 6.23  | 1850 | 0.3532          | 64.9207 | 58.2827 | 64.8053 | 64.8903   | 18.7872 |
| 0.0222        | 6.48  | 1924 | 0.3543          | 64.902  | 58.3086 | 64.793  | 64.8973   | 18.7736 |
| 0.0203        | 6.73  | 1998 | 0.3628          | 65.1022 | 58.7138 | 64.9734 | 65.0891   | 18.7720 |
| 0.0218        | 6.98  | 2072 | 0.3599          | 64.9409 | 58.387  | 64.7925 | 64.9157   | 18.7720 |
| 0.0156        | 7.23  | 2146 | 0.3802          | 65.1242 | 58.8116 | 64.9962 | 65.1097   | 18.7736 |
| 0.013         | 7.47  | 2220 | 0.3845          | 64.9358 | 58.4528 | 64.8099 | 64.925    | 18.7703 |
| 0.0114        | 7.72  | 2294 | 0.3913          | 64.9827 | 58.6449 | 64.863  | 64.9661   | 18.7720 |
| 0.0125        | 7.97  | 2368 | 0.3886          | 65.0031 | 58.5507 | 64.8805 | 64.9845   | 18.7720 |


### 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-large-gecfirst-e8-b16", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

mt5-large-gecfirst-e8-b16
=========================


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


* Loss: 0.2672
* Rouge1: 64.1391
* Rouge2: 56.9117
* Rougel: 64.0719
* Rougelsum: 64.1665
* Gen Len: 18.7753


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 #has_space #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