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# predict-perception-bertino-focus-object

This model is a fine-tuned version of [indigo-ai/BERTino](https://huggingface.co/indigo-ai/BERTino) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2766
- R2: 0.5460

## 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: 0.0001
- train_batch_size: 20
- eval_batch_size: 8
- seed: 1996
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 47

### Training results

| Training Loss | Epoch | Step | Validation Loss | R2     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.4798        | 1.0   | 14   | 0.4519          | 0.2581 |
| 0.2481        | 2.0   | 28   | 0.3042          | 0.5007 |
| 0.12          | 3.0   | 42   | 0.3746          | 0.3851 |
| 0.0969        | 4.0   | 56   | 0.3186          | 0.4770 |
| 0.0907        | 5.0   | 70   | 0.3727          | 0.3882 |
| 0.0673        | 6.0   | 84   | 0.2847          | 0.5327 |
| 0.0457        | 7.0   | 98   | 0.3141          | 0.4844 |
| 0.0431        | 8.0   | 112  | 0.3369          | 0.4470 |
| 0.028         | 9.0   | 126  | 0.3039          | 0.5012 |
| 0.0244        | 10.0  | 140  | 0.2964          | 0.5135 |
| 0.0201        | 11.0  | 154  | 0.3072          | 0.4958 |
| 0.0153        | 12.0  | 168  | 0.3049          | 0.4995 |
| 0.0155        | 13.0  | 182  | 0.2924          | 0.5201 |
| 0.015         | 14.0  | 196  | 0.2585          | 0.5757 |
| 0.0181        | 15.0  | 210  | 0.3258          | 0.4652 |
| 0.0136        | 16.0  | 224  | 0.3142          | 0.4842 |
| 0.0105        | 17.0  | 238  | 0.2536          | 0.5837 |
| 0.0104        | 18.0  | 252  | 0.2407          | 0.6050 |
| 0.0107        | 19.0  | 266  | 0.2727          | 0.5524 |
| 0.0084        | 20.0  | 280  | 0.3117          | 0.4883 |
| 0.0102        | 21.0  | 294  | 0.2999          | 0.5078 |
| 0.0074        | 22.0  | 308  | 0.3018          | 0.5047 |
| 0.0068        | 23.0  | 322  | 0.2826          | 0.5361 |
| 0.0054        | 24.0  | 336  | 0.2804          | 0.5398 |
| 0.0044        | 25.0  | 350  | 0.2912          | 0.5220 |
| 0.0048        | 26.0  | 364  | 0.2813          | 0.5382 |
| 0.005         | 27.0  | 378  | 0.2933          | 0.5186 |
| 0.0046        | 28.0  | 392  | 0.2820          | 0.5371 |
| 0.004         | 29.0  | 406  | 0.2717          | 0.5541 |
| 0.0054        | 30.0  | 420  | 0.2717          | 0.5540 |
| 0.0042        | 31.0  | 434  | 0.2699          | 0.5570 |
| 0.0033        | 32.0  | 448  | 0.2630          | 0.5684 |
| 0.0038        | 33.0  | 462  | 0.2578          | 0.5767 |
| 0.0032        | 34.0  | 476  | 0.2687          | 0.5589 |
| 0.004         | 35.0  | 490  | 0.2737          | 0.5507 |
| 0.0031        | 36.0  | 504  | 0.2753          | 0.5481 |
| 0.0037        | 37.0  | 518  | 0.2819          | 0.5373 |
| 0.0034        | 38.0  | 532  | 0.2759          | 0.5471 |
| 0.0034        | 39.0  | 546  | 0.2835          | 0.5347 |
| 0.0029        | 40.0  | 560  | 0.2814          | 0.5381 |
| 0.0033        | 41.0  | 574  | 0.2801          | 0.5403 |
| 0.0025        | 42.0  | 588  | 0.2759          | 0.5472 |
| 0.0029        | 43.0  | 602  | 0.2790          | 0.5421 |
| 0.0028        | 44.0  | 616  | 0.2801          | 0.5401 |
| 0.003         | 45.0  | 630  | 0.2772          | 0.5451 |
| 0.0028        | 46.0  | 644  | 0.2764          | 0.5463 |
| 0.0026        | 47.0  | 658  | 0.2766          | 0.5460 |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2+cu113
- Datasets 1.18.3
- Tokenizers 0.11.0

{"license": "mit", "tags": ["generated_from_trainer"], "model-index": [{"name": "predict-perception-bertino-focus-object", "results": []}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

predict-perception-bertino-focus-object
=======================================


This model is a fine-tuned version of indigo-ai/BERTino on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2766
* R2: 0.5460


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: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 47


### Training results



### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 47 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 47 ### Training results ### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 20
* eval\_batch\_size: 8
* seed: 1996
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 47### Training results### Framework versions


* Transformers 4.16.2
* Pytorch 1.10.2+cu113
* Datasets 1.18.3
* Tokenizers 0.11.0