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# flan-t5-base-fce-e8-b16

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3114
- Rouge1: 86.9035
- Rouge2: 79.2645
- Rougel: 86.4197
- Rougelsum: 86.4231
- Gen Len: 14.8850

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.4128        | 0.23  | 400   | 0.3457          | 86.8983 | 79.1632 | 86.3755 | 86.3944   | 14.8435 |
| 0.3783        | 0.45  | 800   | 0.3469          | 86.8995 | 78.8428 | 86.3368 | 86.3283   | 14.8955 |
| 0.3627        | 0.68  | 1200  | 0.3114          | 86.9035 | 79.2645 | 86.4197 | 86.4231   | 14.8850 |
| 0.3484        | 0.9   | 1600  | 0.3239          | 87.2292 | 79.8056 | 86.7218 | 86.7237   | 14.8759 |
| 0.2696        | 1.13  | 2000  | 0.3419          | 87.15   | 79.6016 | 86.6082 | 86.6241   | 14.8959 |
| 0.22          | 1.35  | 2400  | 0.3270          | 87.0232 | 79.4806 | 86.5137 | 86.5173   | 14.8868 |
| 0.2327        | 1.58  | 2800  | 0.3185          | 87.1028 | 79.6758 | 86.5985 | 86.6221   | 14.9005 |
| 0.2354        | 1.81  | 3200  | 0.3125          | 87.143  | 79.786  | 86.6545 | 86.6788   | 14.9010 |
| 0.2177        | 2.03  | 3600  | 0.3292          | 87.0858 | 79.5707 | 86.5451 | 86.5456   | 14.9133 |
| 0.1347        | 2.26  | 4000  | 0.3342          | 87.1768 | 79.9161 | 86.6402 | 86.6666   | 14.9142 |
| 0.1411        | 2.48  | 4400  | 0.3456          | 87.1049 | 79.9438 | 86.6152 | 86.6265   | 14.9110 |
| 0.1487        | 2.71  | 4800  | 0.3393          | 86.5182 | 78.468  | 86.0005 | 86.0283   | 14.8813 |
| 0.1498        | 2.93  | 5200  | 0.3347          | 87.2024 | 79.7098 | 86.6782 | 86.6904   | 14.8859 |
| 0.1055        | 3.16  | 5600  | 0.4027          | 87.1281 | 79.799  | 86.5714 | 86.5965   | 14.9105 |
| 0.0862        | 3.39  | 6000  | 0.4046          | 87.2721 | 79.8755 | 86.6838 | 86.6956   | 14.9073 |
| 0.0894        | 3.61  | 6400  | 0.3776          | 87.1508 | 79.865  | 86.6178 | 86.6424   | 14.8946 |
| 0.0942        | 3.84  | 6800  | 0.3781          | 87.2854 | 80.0876 | 86.7694 | 86.7867   | 14.8927 |
| 0.0816        | 4.06  | 7200  | 0.4300          | 87.3854 | 80.1162 | 86.8398 | 86.8446   | 14.8978 |
| 0.0582        | 4.29  | 7600  | 0.4201          | 87.2594 | 80.1824 | 86.7653 | 86.7807   | 14.9019 |
| 0.0588        | 4.51  | 8000  | 0.4129          | 87.3373 | 80.1802 | 86.8332 | 86.8414   | 14.9014 |
| 0.0571        | 4.74  | 8400  | 0.4437          | 87.2985 | 80.0215 | 86.8171 | 86.8238   | 14.8946 |
| 0.0587        | 4.97  | 8800  | 0.4019          | 87.2321 | 80.0933 | 86.6888 | 86.6931   | 14.9105 |
| 0.0381        | 5.19  | 9200  | 0.4822          | 87.2798 | 80.1822 | 86.7799 | 86.7886   | 14.9014 |
| 0.0378        | 5.42  | 9600  | 0.4831          | 87.409  | 80.3418 | 86.8845 | 86.8844   | 14.8927 |
| 0.0368        | 5.64  | 10000 | 0.4809          | 87.2276 | 79.9415 | 86.6776 | 86.6833   | 14.9105 |
| 0.0359        | 5.87  | 10400 | 0.4964          | 87.2916 | 80.1468 | 86.7693 | 86.7704   | 14.9028 |
| 0.0311        | 6.09  | 10800 | 0.5266          | 87.3443 | 80.1762 | 86.7852 | 86.7825   | 14.8991 |
| 0.0225        | 6.32  | 11200 | 0.5550          | 87.3142 | 80.2689 | 86.7856 | 86.7884   | 14.9037 |
| 0.0239        | 6.55  | 11600 | 0.5308          | 87.4003 | 80.2637 | 86.8373 | 86.8356   | 14.9023 |
| 0.0236        | 6.77  | 12000 | 0.5490          | 87.3865 | 80.3184 | 86.8563 | 86.8626   | 14.9037 |
| 0.0223        | 7.0   | 12400 | 0.5454          | 87.3842 | 80.2875 | 86.8109 | 86.8293   | 14.9055 |
| 0.0164        | 7.22  | 12800 | 0.5818          | 87.4641 | 80.3669 | 86.8908 | 86.9062   | 14.8964 |
| 0.0155        | 7.45  | 13200 | 0.5927          | 87.4191 | 80.3356 | 86.8541 | 86.8718   | 14.9014 |
| 0.0152        | 7.67  | 13600 | 0.5990          | 87.4257 | 80.2974 | 86.8481 | 86.8589   | 14.9005 |
| 0.0144        | 7.9   | 14000 | 0.6084          | 87.4754 | 80.3558 | 86.9086 | 86.9184   | 14.9014 |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.11.0a0+b6df043
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "flan-t5-base-fce-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-fce-e8-b16
=======================


This model is a fine-tuned version of google/flan-t5-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3114
* Rouge1: 86.9035
* Rouge2: 79.2645
* Rougel: 86.4197
* Rougelsum: 86.4231
* Gen Len: 14.8850


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 4.28.1
* Pytorch 1.11.0a0+b6df043
* Datasets 2.12.0
* Tokenizers 0.13.3



### 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 4.28.1
* Pytorch 1.11.0a0+b6df043
* Datasets 2.12.0
* Tokenizers 0.13.3
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 4.28.1
* Pytorch 1.11.0a0+b6df043
* Datasets 2.12.0
* Tokenizers 0.13.3