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# flan-t5-base-gecfirst-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: 0.2233
- Rouge1: 42.0185
- Rouge2: 34.0704
- Rougel: 42.0403
- Rougelsum: 41.8957
- Gen Len: 18.9865

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.9817        | 0.25  | 74   | 0.4035          | 38.3182 | 28.427  | 38.3215 | 38.2591   | 18.9882 |
| 0.6805        | 0.5   | 148  | 0.3467          | 39.9659 | 30.9972 | 40.04   | 39.9619   | 18.9831 |
| 0.5885        | 0.75  | 222  | 0.3205          | 40.4848 | 31.33   | 40.4959 | 40.3976   | 18.9797 |
| 0.5476        | 1.0   | 296  | 0.2869          | 40.2589 | 31.6407 | 40.3592 | 40.223    | 18.9831 |
| 0.4504        | 1.25  | 370  | 0.2754          | 40.7626 | 31.8985 | 40.755  | 40.6406   | 18.9831 |
| 0.4463        | 1.49  | 444  | 0.2650          | 40.908  | 32.2358 | 40.9207 | 40.8062   | 18.9831 |
| 0.4155        | 1.74  | 518  | 0.2561          | 41.056  | 32.4906 | 41.029  | 40.9401   | 18.9831 |
| 0.3948        | 1.99  | 592  | 0.2493          | 41.1813 | 32.7917 | 41.2183 | 41.1256   | 18.9831 |
| 0.329         | 2.24  | 666  | 0.2413          | 41.8005 | 33.7235 | 41.88   | 41.7556   | 18.9831 |
| 0.3195        | 2.49  | 740  | 0.2390          | 41.5207 | 33.2502 | 41.5599 | 41.4291   | 18.9848 |
| 0.3148        | 2.74  | 814  | 0.2344          | 41.5913 | 33.398  | 41.614  | 41.4909   | 18.9831 |
| 0.316         | 2.99  | 888  | 0.2266          | 41.6858 | 33.7369 | 41.731  | 41.6293   | 18.9831 |
| 0.2498        | 3.24  | 962  | 0.2353          | 41.7077 | 33.3652 | 41.7111 | 41.6256   | 18.9848 |
| 0.2534        | 3.49  | 1036 | 0.2299          | 41.8645 | 33.9926 | 41.9435 | 41.8168   | 18.9848 |
| 0.2435        | 3.74  | 1110 | 0.2233          | 42.0185 | 34.0704 | 42.0403 | 41.8957   | 18.9865 |
| 0.2514        | 3.99  | 1184 | 0.2292          | 41.9069 | 33.8917 | 41.9112 | 41.7937   | 18.9831 |
| 0.193         | 4.24  | 1258 | 0.2462          | 41.9671 | 34.0261 | 42.024  | 41.9178   | 18.9831 |
| 0.1927        | 4.48  | 1332 | 0.2322          | 42.2226 | 34.6158 | 42.3306 | 42.1946   | 18.9848 |
| 0.1984        | 4.73  | 1406 | 0.2278          | 41.9762 | 34.0828 | 41.999  | 41.9107   | 18.9848 |
| 0.1929        | 4.98  | 1480 | 0.2299          | 41.8244 | 33.831  | 41.8673 | 41.7786   | 18.9848 |
| 0.1522        | 5.23  | 1554 | 0.2432          | 41.9142 | 33.9634 | 41.9635 | 41.859    | 18.9848 |
| 0.1509        | 5.48  | 1628 | 0.2408          | 41.707  | 33.6909 | 41.7144 | 41.6345   | 18.9831 |
| 0.1457        | 5.73  | 1702 | 0.2426          | 42.1729 | 34.2971 | 42.2318 | 42.119    | 18.9848 |
| 0.1497        | 5.98  | 1776 | 0.2386          | 42.1408 | 34.3303 | 42.148  | 42.0599   | 18.9865 |
| 0.1195        | 6.23  | 1850 | 0.2627          | 41.897  | 34.0092 | 41.9336 | 41.8262   | 18.9865 |
| 0.1145        | 6.48  | 1924 | 0.2560          | 41.8456 | 33.7951 | 41.8578 | 41.7709   | 18.9865 |
| 0.1198        | 6.73  | 1998 | 0.2525          | 41.8393 | 33.6033 | 41.8313 | 41.7505   | 18.9831 |
| 0.114         | 6.98  | 2072 | 0.2524          | 41.8194 | 33.7992 | 41.8752 | 41.775    | 18.9848 |
| 0.1           | 7.23  | 2146 | 0.2690          | 41.9724 | 33.9339 | 42.0248 | 41.9444   | 18.9848 |
| 0.0948        | 7.47  | 2220 | 0.2715          | 41.8806 | 33.9232 | 41.9392 | 41.8432   | 18.9848 |
| 0.0947        | 7.72  | 2294 | 0.2722          | 41.8981 | 33.8642 | 41.9622 | 41.877    | 18.9848 |
| 0.0904        | 7.97  | 2368 | 0.2705          | 41.8596 | 33.9216 | 41.915  | 41.8342   | 18.9848 |


### 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-gecfirst-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-gecfirst-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: 0.2233
* Rouge1: 42.0185
* Rouge2: 34.0704
* Rougel: 42.0403
* Rougelsum: 41.8957
* Gen Len: 18.9865


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