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# flan-t5-base-clang8-e8-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: 0.3295
- Rouge1: 81.7467
- Rouge2: 75.6203
- Rougel: 81.3074
- Rougelsum: 81.3474
- Gen Len: 16.7252

## 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 |
|:-------------:|:-----:|:-------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.2375        | 0.34  | 50000   | 0.3787          | 79.3834 | 72.8125 | 78.8797 | 78.9476   | 16.4064 |
| 0.193         | 0.68  | 100000  | 0.3648          | 80.5738 | 74.213  | 80.1251 | 80.1723   | 16.6474 |
| 0.1741        | 1.02  | 150000  | 0.3528          | 80.3142 | 73.9623 | 79.8468 | 79.9051   | 16.5495 |
| 0.1472        | 1.36  | 200000  | 0.3404          | 81.6263 | 75.4272 | 81.2208 | 81.2709   | 16.5801 |
| 0.1438        | 1.7   | 250000  | 0.3295          | 81.7467 | 75.6203 | 81.3074 | 81.3474   | 16.7252 |
| 0.1366        | 2.04  | 300000  | 0.3335          | 82.2013 | 76.1543 | 81.8099 | 81.8542   | 16.6817 |
| 0.1149        | 2.38  | 350000  | 0.3388          | 82.0549 | 76.0367 | 81.612  | 81.6705   | 16.6349 |
| 0.1158        | 2.72  | 400000  | 0.3380          | 81.8668 | 75.7396 | 81.3624 | 81.4208   | 16.6718 |
| 0.1096        | 3.06  | 450000  | 0.3355          | 82.2566 | 76.2443 | 81.8557 | 81.8799   | 16.6314 |
| 0.091         | 3.4   | 500000  | 0.3563          | 81.6493 | 75.5706 | 81.192  | 81.2568   | 16.6118 |
| 0.0929        | 3.74  | 550000  | 0.3457          | 81.8688 | 75.9296 | 81.3592 | 81.4311   | 16.5591 |
| 0.0866        | 4.08  | 600000  | 0.3640          | 82.1338 | 76.0786 | 81.7067 | 81.7521   | 16.6241 |
| 0.071         | 4.42  | 650000  | 0.3623          | 82.1396 | 76.1338 | 81.7451 | 81.7737   | 16.6887 |
| 0.0726        | 4.76  | 700000  | 0.3504          | 82.2745 | 76.2648 | 81.875  | 81.9091   | 16.6860 |
| 0.0663        | 5.1   | 750000  | 0.3918          | 82.0424 | 76.092  | 81.6495 | 81.6595   | 16.6449 |
| 0.0535        | 5.44  | 800000  | 0.3818          | 82.1967 | 76.2488 | 81.7716 | 81.807    | 16.6835 |
| 0.0544        | 5.78  | 850000  | 0.3857          | 81.966  | 75.9981 | 81.5936 | 81.6119   | 16.6449 |
| 0.0483        | 6.13  | 900000  | 0.4260          | 82.3128 | 76.3527 | 81.908  | 81.9394   | 16.6730 |
| 0.0388        | 6.47  | 950000  | 0.4271          | 82.2929 | 76.3275 | 81.8769 | 81.9049   | 16.7122 |
| 0.0387        | 6.81  | 1000000 | 0.4203          | 82.3302 | 76.4099 | 81.9579 | 81.9744   | 16.6992 |
| 0.0338        | 7.15  | 1050000 | 0.4709          | 82.1839 | 76.2599 | 81.7796 | 81.8151   | 16.6737 |
| 0.0277        | 7.49  | 1100000 | 0.4756          | 82.2163 | 76.2606 | 81.7974 | 81.8287   | 16.6691 |
| 0.0271        | 7.83  | 1150000 | 0.4760          | 82.1215 | 76.1794 | 81.7053 | 81.7387   | 16.6965 |


### 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-e8-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-e8-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: 0.3295
* Rouge1: 81.7467
* Rouge2: 75.6203
* Rougel: 81.3074
* Rougelsum: 81.3474
* Gen Len: 16.7252


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 4.27.4
* 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: 8 ### 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: 8 ### 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: 8### Training results### Framework versions


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