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# flan-t5-base-extraction-cnndm_40000-all-hint_precision-ep50-nonstop

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: 1.6648
- Hint Hit Num: 2.3792
- Hint Precision: 0.4254
- Num: 5.5651
- Gen Len: 18.9983

## 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: 2e-05
- train_batch_size: 60
- eval_batch_size: 400
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Hint Hit Num | Hint Precision | Num    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------------:|:--------------:|:------:|:-------:|
| 2.1311        | 0.75  | 500   | 1.7662          | 2.1274       | 0.4051         | 5.2401 | 18.998  |
| 1.9622        | 1.5   | 1000  | 1.7248          | 2.209        | 0.4135         | 5.3367 | 18.9994 |
| 1.9108        | 2.25  | 1500  | 1.6995          | 2.2522       | 0.4187         | 5.3647 | 18.9999 |
| 1.8855        | 3.0   | 2000  | 1.6806          | 2.246        | 0.4156         | 5.3827 | 18.9999 |
| 1.8518        | 3.75  | 2500  | 1.6778          | 2.2829       | 0.4206         | 5.4082 | 18.9999 |
| 1.8324        | 4.5   | 3000  | 1.6741          | 2.2665       | 0.4175         | 5.4088 | 18.9999 |
| 1.8211        | 5.25  | 3500  | 1.6639          | 2.2819       | 0.4184         | 5.433  | 18.9999 |
| 1.7971        | 6.0   | 4000  | 1.6594          | 2.2896       | 0.4192         | 5.4375 | 18.9999 |
| 1.7788        | 6.75  | 4500  | 1.6554          | 2.3157       | 0.4224         | 5.4634 | 19.0    |
| 1.7755        | 7.5   | 5000  | 1.6550          | 2.3118       | 0.4216         | 5.4629 | 18.9999 |
| 1.7543        | 8.25  | 5500  | 1.6501          | 2.3345       | 0.4235         | 5.4905 | 18.9999 |
| 1.7491        | 9.0   | 6000  | 1.6534          | 2.3242       | 0.422          | 5.4823 | 18.9997 |
| 1.7317        | 9.75  | 6500  | 1.6483          | 2.2962       | 0.4178         | 5.4673 | 18.9999 |
| 1.7239        | 10.49 | 7000  | 1.6539          | 2.3283       | 0.4219         | 5.4958 | 18.9999 |
| 1.7109        | 11.24 | 7500  | 1.6495          | 2.3064       | 0.4198         | 5.4751 | 18.9997 |
| 1.7072        | 11.99 | 8000  | 1.6519          | 2.3465       | 0.4233         | 5.5209 | 18.999  |
| 1.6938        | 12.74 | 8500  | 1.6561          | 2.3086       | 0.4188         | 5.4821 | 18.999  |
| 1.6862        | 13.49 | 9000  | 1.6487          | 2.3524       | 0.423          | 5.5348 | 18.9991 |
| 1.6777        | 14.24 | 9500  | 1.6584          | 2.3453       | 0.4233         | 5.5088 | 18.999  |
| 1.6745        | 14.99 | 10000 | 1.6519          | 2.3062       | 0.418          | 5.4853 | 18.999  |
| 1.6623        | 15.74 | 10500 | 1.6553          | 2.3196       | 0.4202         | 5.4929 | 18.9992 |
| 1.6518        | 16.49 | 11000 | 1.6523          | 2.3467       | 0.4218         | 5.5332 | 18.999  |
| 1.651         | 17.24 | 11500 | 1.6568          | 2.36         | 0.4239         | 5.5397 | 18.999  |
| 1.6446        | 17.99 | 12000 | 1.6574          | 2.3526       | 0.423          | 5.5349 | 18.9991 |
| 1.6334        | 18.74 | 12500 | 1.6632          | 2.3106       | 0.4185         | 5.4907 | 18.9986 |
| 1.6322        | 19.49 | 13000 | 1.6590          | 2.3285       | 0.4199         | 5.5171 | 18.9987 |
| 1.6218        | 20.24 | 13500 | 1.6601          | 2.3377       | 0.4199         | 5.535  | 18.9993 |
| 1.6189        | 20.99 | 14000 | 1.6596          | 2.3493       | 0.4213         | 5.5447 | 18.9987 |
| 1.61          | 21.74 | 14500 | 1.6648          | 2.3792       | 0.4254         | 5.5651 | 18.9983 |
| 1.6064        | 22.49 | 15000 | 1.6668          | 2.3556       | 0.422          | 5.5521 | 18.9979 |
| 1.6004        | 23.24 | 15500 | 1.6674          | 2.3374       | 0.4195         | 5.5356 | 18.9987 |
| 1.597         | 23.99 | 16000 | 1.6654          | 2.3487       | 0.4203         | 5.5595 | 18.9987 |
| 1.5906        | 24.74 | 16500 | 1.6705          | 2.3634       | 0.4227         | 5.5575 | 18.9983 |
| 1.5851        | 25.49 | 17000 | 1.6690          | 2.3609       | 0.4229         | 5.5495 | 18.9983 |
| 1.5856        | 26.24 | 17500 | 1.6716          | 2.3444       | 0.4213         | 5.5376 | 18.9987 |
| 1.577         | 26.99 | 18000 | 1.6708          | 2.3693       | 0.4233         | 5.5631 | 18.9987 |
| 1.5734        | 27.74 | 18500 | 1.6707          | 2.3796       | 0.4236         | 5.5854 | 18.9983 |
| 1.5665        | 28.49 | 19000 | 1.6694          | 2.3639       | 0.4219         | 5.5698 | 18.9987 |
| 1.5666        | 29.24 | 19500 | 1.6798          | 2.3609       | 0.4221         | 5.5592 | 18.9987 |
| 1.564         | 29.99 | 20000 | 1.6778          | 2.3535       | 0.4204         | 5.5679 | 18.9987 |
| 1.5574        | 30.73 | 20500 | 1.6786          | 2.3476       | 0.4196         | 5.564  | 18.9987 |
| 1.5549        | 31.48 | 21000 | 1.6787          | 2.3658       | 0.4213         | 5.5862 | 18.999  |
| 1.5522        | 32.23 | 21500 | 1.6830          | 2.356        | 0.4212         | 5.5619 | 18.999  |
| 1.5485        | 32.98 | 22000 | 1.6784          | 2.3659       | 0.4218         | 5.5768 | 18.9987 |
| 1.5425        | 33.73 | 22500 | 1.6836          | 2.371        | 0.4222         | 5.5849 | 18.998  |
| 1.5449        | 34.48 | 23000 | 1.6817          | 2.365        | 0.4218         | 5.573  | 18.9985 |
| 1.5395        | 35.23 | 23500 | 1.6855          | 2.3633       | 0.4219         | 5.5694 | 18.9984 |
| 1.5358        | 35.98 | 24000 | 1.6834          | 2.3674       | 0.4221         | 5.5788 | 18.9988 |
| 1.5323        | 36.73 | 24500 | 1.6887          | 2.3725       | 0.4225         | 5.5857 | 18.9988 |
| 1.5298        | 37.48 | 25000 | 1.6861          | 2.3656       | 0.4207         | 5.5888 | 18.9991 |
| 1.526         | 38.23 | 25500 | 1.6905          | 2.3535       | 0.4202         | 5.5687 | 18.9991 |
| 1.5329        | 38.98 | 26000 | 1.6890          | 2.371        | 0.4218         | 5.5905 | 18.9988 |
| 1.5254        | 39.73 | 26500 | 1.6885          | 2.371        | 0.4223         | 5.5827 | 18.9989 |
| 1.5245        | 40.48 | 27000 | 1.6908          | 2.3615       | 0.4209         | 5.5781 | 18.9988 |
| 1.5166        | 41.23 | 27500 | 1.6907          | 2.3734       | 0.4214         | 5.598  | 18.9989 |
| 1.5225        | 41.98 | 28000 | 1.6904          | 2.3739       | 0.4219         | 5.5945 | 18.9989 |
| 1.5149        | 42.73 | 28500 | 1.6916          | 2.3768       | 0.4229         | 5.5913 | 18.9989 |
| 1.5178        | 43.48 | 29000 | 1.6938          | 2.3654       | 0.4214         | 5.5826 | 18.9991 |
| 1.5212        | 44.23 | 29500 | 1.6928          | 2.3674       | 0.4219         | 5.5821 | 18.9988 |
| 1.5136        | 44.98 | 30000 | 1.6917          | 2.3781       | 0.4227         | 5.5952 | 18.999  |
| 1.5097        | 45.73 | 30500 | 1.6923          | 2.3704       | 0.4218         | 5.5896 | 18.999  |
| 1.5183        | 46.48 | 31000 | 1.6935          | 2.3719       | 0.4217         | 5.5931 | 18.999  |
| 1.5092        | 47.23 | 31500 | 1.6935          | 2.3684       | 0.4216         | 5.5868 | 18.999  |
| 1.5127        | 47.98 | 32000 | 1.6943          | 2.3691       | 0.4218         | 5.5863 | 18.999  |
| 1.5124        | 48.73 | 32500 | 1.6940          | 2.3704       | 0.422          | 5.5874 | 18.9987 |
| 1.5117        | 49.48 | 33000 | 1.6948          | 2.3693       | 0.4217         | 5.587  | 18.9987 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.5.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "flan-t5-base-extraction-cnndm_40000-all-hint_precision-ep50-nonstop", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-base-extraction-cnndm\_40000-all-hint\_precision-ep50-nonstop
=====================================================================


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: 1.6648
* Hint Hit Num: 2.3792
* Hint Precision: 0.4254
* Num: 5.5651
* Gen Len: 18.9983


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: 2e-05
* train\_batch\_size: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 2e-05
* train\_batch\_size: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #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: 2e-05
* train\_batch\_size: 60
* eval\_batch\_size: 400
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 50### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.5.1
* Tokenizers 0.12.1