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# flan-t5-large-fce-e8-b16

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3123
- Rouge1: 87.0781
- Rouge2: 79.8175
- Rougel: 86.6213
- Rougelsum: 86.6385
- Gen Len: 14.8832

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.3761        | 0.23  | 400   | 0.3325          | 86.7053 | 79.1321 | 86.1593 | 86.1958   | 14.8864 |
| 0.3516        | 0.45  | 800   | 0.3201          | 86.8076 | 79.1282 | 86.2981 | 86.3209   | 14.8781 |
| 0.3401        | 0.68  | 1200  | 0.3187          | 86.479  | 78.6505 | 85.9172 | 85.9585   | 14.8800 |
| 0.3283        | 0.9   | 1600  | 0.3123          | 87.0781 | 79.8175 | 86.6213 | 86.6385   | 14.8832 |
| 0.2395        | 1.13  | 2000  | 0.3278          | 86.7979 | 79.3766 | 86.3314 | 86.3581   | 14.9046 |
| 0.1817        | 1.35  | 2400  | 0.3170          | 86.8343 | 79.4019 | 86.3148 | 86.3232   | 14.8964 |
| 0.1962        | 1.58  | 2800  | 0.3138          | 86.8702 | 79.425  | 86.3412 | 86.36     | 14.9069 |
| 0.1971        | 1.81  | 3200  | 0.3191          | 86.8355 | 79.3178 | 86.2974 | 86.322    | 14.8809 |
| 0.1816        | 2.03  | 3600  | 0.3490          | 87.0986 | 79.7312 | 86.6108 | 86.6227   | 14.9142 |
| 0.0975        | 2.26  | 4000  | 0.3534          | 86.7684 | 79.3649 | 86.2755 | 86.2885   | 14.9069 |
| 0.1033        | 2.48  | 4400  | 0.3536          | 86.8978 | 79.714  | 86.4135 | 86.435    | 14.9302 |
| 0.1086        | 2.71  | 4800  | 0.3553          | 86.6286 | 79.3293 | 86.1381 | 86.1686   | 14.9078 |
| 0.1141        | 2.93  | 5200  | 0.3530          | 86.8452 | 79.4178 | 86.2927 | 86.3239   | 14.9010 |
| 0.076         | 3.16  | 5600  | 0.4088          | 86.992  | 79.8179 | 86.5124 | 86.5186   | 14.9096 |
| 0.0595        | 3.39  | 6000  | 0.4052          | 86.8874 | 79.6302 | 86.3643 | 86.3784   | 14.9101 |
| 0.0606        | 3.61  | 6400  | 0.4051          | 86.9236 | 79.5305 | 86.3715 | 86.3959   | 14.9101 |
| 0.0653        | 3.84  | 6800  | 0.3860          | 86.8353 | 79.541  | 86.3249 | 86.3292   | 14.9165 |
| 0.0553        | 4.06  | 7200  | 0.4229          | 86.7788 | 79.5444 | 86.3393 | 86.3468   | 14.8868 |
| 0.0339        | 4.29  | 7600  | 0.4478          | 86.6863 | 79.5215 | 86.216  | 86.2363   | 14.9133 |
| 0.0375        | 4.51  | 8000  | 0.4359          | 86.8412 | 79.668  | 86.3237 | 86.3349   | 14.9229 |
| 0.0376        | 4.74  | 8400  | 0.4459          | 86.8836 | 79.682  | 86.3993 | 86.4062   | 14.9069 |
| 0.0372        | 4.97  | 8800  | 0.4324          | 86.6833 | 79.5114 | 86.1856 | 86.2031   | 14.9197 |
| 0.023         | 5.19  | 9200  | 0.4930          | 86.9595 | 79.8244 | 86.4103 | 86.4373   | 14.9279 |
| 0.0211        | 5.42  | 9600  | 0.4927          | 87.0212 | 79.8707 | 86.5054 | 86.5117   | 14.9320 |
| 0.0215        | 5.64  | 10000 | 0.4915          | 86.9495 | 79.8479 | 86.458  | 86.4632   | 14.9115 |
| 0.0205        | 5.87  | 10400 | 0.4919          | 86.8966 | 79.7666 | 86.424  | 86.4482   | 14.9069 |
| 0.0169        | 6.09  | 10800 | 0.5415          | 87.1119 | 80.0504 | 86.6205 | 86.6255   | 14.9083 |
| 0.0116        | 6.32  | 11200 | 0.5767          | 87.1828 | 80.2547 | 86.6809 | 86.6742   | 14.9215 |
| 0.0113        | 6.55  | 11600 | 0.5799          | 87.2494 | 80.2853 | 86.7412 | 86.761    | 14.9147 |
| 0.0103        | 6.77  | 12000 | 0.6036          | 87.1081 | 80.1873 | 86.6086 | 86.6176   | 14.9251 |
| 0.0106        | 7.0   | 12400 | 0.5821          | 87.1489 | 80.1987 | 86.654  | 86.6694   | 14.9242 |
| 0.0064        | 7.22  | 12800 | 0.6325          | 87.2026 | 80.2043 | 86.6988 | 86.704    | 14.9197 |
| 0.0056        | 7.45  | 13200 | 0.6878          | 87.184  | 80.1382 | 86.6798 | 86.7049   | 14.9188 |
| 0.0061        | 7.67  | 13600 | 0.6888          | 87.2465 | 80.1602 | 86.7407 | 86.7459   | 14.9201 |
| 0.0057        | 7.9   | 14000 | 0.6922          | 87.2584 | 80.2614 | 86.7806 | 86.7948   | 14.9201 |


### 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-large-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-large-fce-e8-b16
========================


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


* Loss: 0.3123
* Rouge1: 87.0781
* Rouge2: 79.8175
* Rougel: 86.6213
* Rougelsum: 86.6385
* Gen Len: 14.8832


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