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# flan-t5-base

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0724
- Rouge1 Precision: 0.0
- Rouge1 Recall: 0.0
- Rouge1 Fmeasure: 0.0
- Rouge2 Precision: 0.0
- Rouge2 Recall: 0.0
- Rouge2 Fmeasure: 0.0
- Rougel Precision: 0.0
- Rougel Recall: 0.0
- Rougel Fmeasure: 0.0
- Rougelsum Precision: 0.0
- Rougelsum Recall: 0.0
- Rougelsum Fmeasure: 0.0
- Bleu-1: 0.0
- Bleu-2: 0.0
- Bleu-3: 0.0
- Bleu-4: 0.0
- Meteor: 0.0006

## 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: 5e-05
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Rougel Precision | Rougel Recall | Rougel Fmeasure | Rougelsum Precision | Rougelsum Recall | Rougelsum Fmeasure | Bleu-1 | Bleu-2 | Bleu-3 | Bleu-4 | Meteor |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:-------------------:|:----------------:|:------------------:|:------:|:------:|:------:|:------:|:------:|
| 0.0641        | 1.0   | 10830 | 0.0726          | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0                 | 0.0              | 0.0                | 0.0    | 0.0    | 0.0    | 0.0    | 0.0    |
| 0.0613        | 2.0   | 21660 | 0.0759          | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0                 | 0.0              | 0.0                | 0.0    | 0.0    | 0.0    | 0.0    | 0.0003 |
| 0.0628        | 3.0   | 32490 | 0.0755          | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0                 | 0.0              | 0.0                | 0.0    | 0.0    | 0.0    | 0.0    | 0.0004 |
| 0.0631        | 4.0   | 43320 | 0.0724          | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0                 | 0.0              | 0.0                | 0.0    | 0.0    | 0.0    | 0.0    | 0.0006 |
| 0.0597        | 5.0   | 54150 | 0.0741          | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0              | 0.0           | 0.0             | 0.0                 | 0.0              | 0.0                | 0.0    | 0.0    | 0.0    | 0.0    | 0.0006 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "flan-t5-base", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-base
============


This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0724
* Rouge1 Precision: 0.0
* Rouge1 Recall: 0.0
* Rouge1 Fmeasure: 0.0
* Rouge2 Precision: 0.0
* Rouge2 Recall: 0.0
* Rouge2 Fmeasure: 0.0
* Rougel Precision: 0.0
* Rougel Recall: 0.0
* Rougel Fmeasure: 0.0
* Rougelsum Precision: 0.0
* Rougelsum Recall: 0.0
* Rougelsum Fmeasure: 0.0
* Bleu-1: 0.0
* Bleu-2: 0.0
* Bleu-3: 0.0
* Bleu-4: 0.0
* Meteor: 0.0006


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: 5e-05
* train\_batch\_size: 5
* eval\_batch\_size: 5
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 5
* eval\_batch\_size: 5
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 5
* eval\_batch\_size: 5
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 5 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0
* Datasets 2.1.0
* Tokenizers 0.13.3