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# predict-perception-bertino-cause-none

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: 0.1988
- R2: 0.4467

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.56          | 1.0   | 14   | 0.3460          | 0.0372 |
| 0.3752        | 2.0   | 28   | 0.3082          | 0.1423 |
| 0.147         | 3.0   | 42   | 0.2299          | 0.3603 |
| 0.0961        | 4.0   | 56   | 0.3254          | 0.0944 |
| 0.0859        | 5.0   | 70   | 0.2650          | 0.2625 |
| 0.0735        | 6.0   | 84   | 0.2430          | 0.3237 |
| 0.042         | 7.0   | 98   | 0.2567          | 0.2856 |
| 0.0328        | 8.0   | 112  | 0.2092          | 0.4180 |
| 0.028         | 9.0   | 126  | 0.2262          | 0.3706 |
| 0.0237        | 10.0  | 140  | 0.2170          | 0.3960 |
| 0.0235        | 11.0  | 154  | 0.2137          | 0.4054 |
| 0.0195        | 12.0  | 168  | 0.2009          | 0.4409 |
| 0.0217        | 13.0  | 182  | 0.2001          | 0.4431 |
| 0.0176        | 14.0  | 196  | 0.2123          | 0.4091 |
| 0.0226        | 15.0  | 210  | 0.2076          | 0.4224 |
| 0.019         | 16.0  | 224  | 0.1920          | 0.4657 |
| 0.0122        | 17.0  | 238  | 0.2301          | 0.3598 |
| 0.0121        | 18.0  | 252  | 0.2092          | 0.4178 |
| 0.0112        | 19.0  | 266  | 0.2038          | 0.4329 |
| 0.0081        | 20.0  | 280  | 0.2008          | 0.4411 |
| 0.0079        | 21.0  | 294  | 0.1930          | 0.4631 |
| 0.0083        | 22.0  | 308  | 0.2076          | 0.4222 |
| 0.0061        | 23.0  | 322  | 0.2036          | 0.4334 |
| 0.0057        | 24.0  | 336  | 0.1986          | 0.4472 |
| 0.0059        | 25.0  | 350  | 0.2079          | 0.4215 |
| 0.0082        | 26.0  | 364  | 0.2125          | 0.4087 |
| 0.0093        | 27.0  | 378  | 0.2096          | 0.4168 |
| 0.0061        | 28.0  | 392  | 0.2129          | 0.4076 |
| 0.005         | 29.0  | 406  | 0.2054          | 0.4284 |
| 0.0058        | 30.0  | 420  | 0.2024          | 0.4368 |
| 0.006         | 31.0  | 434  | 0.1999          | 0.4437 |
| 0.0047        | 32.0  | 448  | 0.1917          | 0.4666 |
| 0.0046        | 33.0  | 462  | 0.2000          | 0.4435 |
| 0.005         | 34.0  | 476  | 0.2003          | 0.4425 |
| 0.0041        | 35.0  | 490  | 0.2057          | 0.4276 |
| 0.0037        | 36.0  | 504  | 0.1985          | 0.4476 |
| 0.0049        | 37.0  | 518  | 0.2029          | 0.4353 |
| 0.0031        | 38.0  | 532  | 0.1963          | 0.4539 |
| 0.0031        | 39.0  | 546  | 0.1957          | 0.4554 |
| 0.0031        | 40.0  | 560  | 0.1962          | 0.4540 |
| 0.0029        | 41.0  | 574  | 0.2000          | 0.4433 |
| 0.0028        | 42.0  | 588  | 0.1986          | 0.4473 |
| 0.0035        | 43.0  | 602  | 0.1972          | 0.4514 |
| 0.0029        | 44.0  | 616  | 0.1984          | 0.4479 |
| 0.0036        | 45.0  | 630  | 0.2005          | 0.4422 |
| 0.0033        | 46.0  | 644  | 0.1994          | 0.4452 |
| 0.0029        | 47.0  | 658  | 0.1988          | 0.4467 |


### 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-cause-none", "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-cause-none
=====================================


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: 0.1988
* R2: 0.4467


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