
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# mt5-base-gecid-e8-b8

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3149
- Rouge1: 63.7794
- Rouge2: 56.8052
- Rougel: 63.71
- Rougelsum: 63.7021
- Gen Len: 18.7580

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4284        | 0.25  | 221  | 0.5336          | 59.2266 | 49.3982 | 59.1131 | 59.1192   | 18.7516 |
| 0.6794        | 0.5   | 442  | 0.5026          | 60.2965 | 51.1698 | 60.2314 | 60.2144   | 18.7550 |
| 0.6054        | 0.75  | 663  | 0.4443          | 61.5746 | 53.2755 | 61.5027 | 61.4981   | 18.7439 |
| 0.5234        | 1.0   | 884  | 0.4024          | 62.0849 | 54.0043 | 61.98   | 61.9795   | 18.7571 |
| 0.4023        | 1.25  | 1105 | 0.3876          | 62.3763 | 54.516  | 62.2915 | 62.2758   | 18.7546 |
| 0.3615        | 1.5   | 1326 | 0.3500          | 62.8309 | 55.2966 | 62.767  | 62.7424   | 18.7550 |
| 0.3464        | 1.75  | 1547 | 0.3758          | 62.9962 | 55.4509 | 62.9335 | 62.9322   | 18.7499 |
| 0.3295        | 2.0   | 1768 | 0.3810          | 62.9764 | 55.2429 | 62.8254 | 62.8139   | 18.7524 |
| 0.234         | 2.25  | 1989 | 0.3433          | 63.4401 | 56.2959 | 63.3721 | 63.3559   | 18.7622 |
| 0.2138        | 2.5   | 2210 | 0.3558          | 63.5914 | 56.5334 | 63.5275 | 63.5203   | 18.7567 |
| 0.2153        | 2.75  | 2431 | 0.3149          | 63.7794 | 56.8052 | 63.71   | 63.7021   | 18.7580 |
| 0.2211        | 3.0   | 2652 | 0.3202          | 64.0491 | 57.399  | 63.9913 | 63.9872   | 18.7584 |
| 0.137         | 3.25  | 2873 | 0.3409          | 64.0702 | 57.3436 | 63.9913 | 63.9988   | 18.7537 |
| 0.1374        | 3.5   | 3094 | 0.3272          | 64.1621 | 57.4838 | 64.0817 | 64.0887   | 18.7486 |
| 0.1419        | 3.75  | 3315 | 0.3237          | 64.3536 | 57.7776 | 64.2516 | 64.2575   | 18.7478 |
| 0.1385        | 4.0   | 3536 | 0.3278          | 64.4918 | 58.0381 | 64.4171 | 64.4095   | 18.7567 |
| 0.0843        | 4.25  | 3757 | 0.3524          | 64.4279 | 57.9151 | 64.3466 | 64.3437   | 18.7503 |
| 0.0869        | 4.5   | 3978 | 0.3484          | 64.6526 | 58.2318 | 64.5719 | 64.5511   | 18.7507 |
| 0.0852        | 4.75  | 4199 | 0.3375          | 64.6296 | 58.3682 | 64.5767 | 64.5826   | 18.7563 |
| 0.0858        | 5.0   | 4420 | 0.3332          | 64.5979 | 58.3381 | 64.5341 | 64.5327   | 18.7524 |
| 0.0546        | 5.25  | 4641 | 0.3699          | 64.7273 | 58.6031 | 64.6666 | 64.6717   | 18.7588 |
| 0.0543        | 5.5   | 4862 | 0.3625          | 64.902  | 58.8353 | 64.8386 | 64.8482   | 18.7588 |
| 0.0514        | 5.75  | 5083 | 0.3566          | 64.7232 | 58.5502 | 64.6608 | 64.6557   | 18.7580 |
| 0.0542        | 6.0   | 5304 | 0.3562          | 64.8116 | 58.7128 | 64.7289 | 64.7468   | 18.7592 |
| 0.0301        | 6.25  | 5525 | 0.3975          | 64.8613 | 58.7115 | 64.7799 | 64.7906   | 18.7575 |
| 0.0344        | 6.5   | 5746 | 0.3938          | 64.9673 | 58.8576 | 64.8817 | 64.8935   | 18.7575 |
| 0.0319        | 6.75  | 5967 | 0.3867          | 64.918  | 58.8365 | 64.8385 | 64.8376   | 18.7597 |
| 0.0315        | 7.0   | 6188 | 0.3793          | 65.0065 | 58.9789 | 64.9387 | 64.9456   | 18.7588 |
| 0.0234        | 7.25  | 6409 | 0.3983          | 64.9348 | 58.9178 | 64.8671 | 64.8776   | 18.7580 |
| 0.022         | 7.5   | 6630 | 0.4099          | 65.0139 | 59.0427 | 64.9463 | 64.9453   | 18.7588 |
| 0.0183        | 7.75  | 6851 | 0.4187          | 64.9696 | 58.9453 | 64.9022 | 64.9074   | 18.7601 |
| 0.0206        | 8.0   | 7072 | 0.4181          | 65.0    | 58.9921 | 64.9346 | 64.94     | 18.7605 |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.11.0a0+b6df043
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "mt5-base-gecid-e8-b8", "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-gecid-e8-b8
====================


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


* Loss: 0.3149
* Rouge1: 63.7794
* Rouge2: 56.8052
* Rougel: 63.71
* Rougelsum: 63.7021
* Gen Len: 18.7580


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: 8
* eval\_batch\_size: 8
* 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 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* 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 0.13.2
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: 8
* eval\_batch\_size: 8
* 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 0.13.2