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# flan-t5-large-clang8-e8-b16

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3695
- Rouge1: 81.5302
- Rouge2: 75.0006
- Rougel: 80.8048
- Rougelsum: 80.8804
- Gen Len: 16.4010

## 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 |
|:-------------:|:-----:|:-------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.2445        | 0.34  | 50000   | 0.4619          | 75.7068 | 68.1664 | 74.9827 | 75.0547   | 15.3599 |
| 0.204         | 0.68  | 100000  | 0.4205          | 78.5266 | 71.5654 | 77.9103 | 77.9927   | 15.7896 |
| 0.1874        | 1.02  | 150000  | 0.3911          | 79.4458 | 72.6087 | 78.9344 | 78.9609   | 16.0050 |
| 0.1632        | 1.36  | 200000  | 0.3829          | 80.8458 | 74.0334 | 80.2669 | 80.294    | 16.1926 |
| 0.1613        | 1.7   | 250000  | 0.4153          | 77.1978 | 70.3072 | 76.6089 | 76.6786   | 15.5472 |
| 0.1563        | 2.04  | 300000  | 0.3695          | 81.5302 | 75.0006 | 80.8048 | 80.8804   | 16.4010 |
| 0.1363        | 2.38  | 350000  | 0.3996          | 78.4903 | 71.72   | 77.8836 | 77.9325   | 15.8473 |
| 0.1364        | 2.72  | 400000  | 0.3952          | 78.9584 | 72.1529 | 78.2906 | 78.3357   | 15.8277 |
| 0.1296        | 3.06  | 450000  | 0.3843          | 78.845  | 71.8678 | 78.1533 | 78.2124   | 15.8288 |
| 0.1116        | 3.4   | 500000  | 0.3839          | 80.9622 | 74.4656 | 80.4038 | 80.4719   | 16.1280 |
| 0.1119        | 3.74  | 550000  | 0.3734          | 80.4889 | 73.7373 | 79.7885 | 79.8515   | 16.1164 |
| 0.1042        | 4.08  | 600000  | 0.3857          | 80.6982 | 73.9657 | 80.1064 | 80.1566   | 16.1577 |
| 0.088         | 4.42  | 650000  | 0.3929          | 79.4607 | 72.7156 | 78.8256 | 78.8513   | 15.8441 |
| 0.0879        | 4.76  | 700000  | 0.3817          | 80.4776 | 73.8007 | 79.796  | 79.8602   | 16.1504 |
| 0.0803        | 5.1   | 750000  | 0.4107          | 80.5342 | 73.8022 | 79.8444 | 79.9184   | 16.1771 |
| 0.0654        | 5.44  | 800000  | 0.4003          | 79.7355 | 73.18   | 79.161  | 79.1934   | 15.9977 |
| 0.0658        | 5.78  | 850000  | 0.4130          | 78.9623 | 72.3575 | 78.2787 | 78.3253   | 15.7458 |
| 0.0573        | 6.13  | 900000  | 0.4490          | 79.4727 | 72.8786 | 78.7881 | 78.8366   | 15.9856 |
| 0.0451        | 6.47  | 950000  | 0.4379          | 80.0433 | 73.4325 | 79.4249 | 79.4754   | 15.9811 |
| 0.0447        | 6.81  | 1000000 | 0.4500          | 80.3675 | 73.7878 | 79.75   | 79.8028   | 16.0735 |
| 0.0381        | 7.15  | 1050000 | 0.5095          | 79.3452 | 72.6912 | 78.7528 | 78.7793   | 15.8832 |
| 0.0299        | 7.49  | 1100000 | 0.4950          | 79.956  | 73.2692 | 79.3025 | 79.3577   | 16.0187 |
| 0.0291        | 7.83  | 1150000 | 0.4987          | 79.4864 | 72.8335 | 78.9    | 78.9366   | 15.9037 |


### 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-large-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-large-clang8-e8-b16
===========================


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


* Loss: 0.3695
* Rouge1: 81.5302
* Rouge2: 75.0006
* Rougel: 80.8048
* Rougelsum: 80.8804
* Gen Len: 16.4010


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