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# flan-t5-base-clang8-e1-b16

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3150
- Rouge1: 82.2657
- Rouge2: 76.3303
- Rougel: 81.8622
- Rougelsum: 81.9329
- Gen Len: 16.6232

## 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: 1

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.227         | 0.34  | 50000  | 0.3619          | 79.9421 | 73.5267 | 79.424  | 79.5292   | 16.1650 |
| 0.1658        | 0.68  | 100000 | 0.3150          | 82.2657 | 76.3303 | 81.8622 | 81.9329   | 16.6232 |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.11.0a0+b6df043
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "flan-t5-base-clang8-e1-b16", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-base-clang8-e1-b16
==========================


This model is a fine-tuned version of google/flan-t5-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3150
* Rouge1: 82.2657
* Rouge2: 76.3303
* Rougel: 81.8622
* Rougelsum: 81.9329
* Gen Len: 16.6232


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: 1


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 1.11.0a0+b6df043
* Datasets 2.11.0
* Tokenizers 0.13.2



### 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: 1 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.11.0a0+b6df043
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #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: 1 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 1.11.0a0+b6df043
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #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: 1### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 1.11.0a0+b6df043
* Datasets 2.11.0
* Tokenizers 0.13.2