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# predict-perception-bertino-cause-concept

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: 0.2035
- R2: -0.3662

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3498        | 1.0   | 14   | 0.1845          | -0.2382 |
| 0.2442        | 2.0   | 28   | 0.1575          | -0.0573 |
| 0.1553        | 3.0   | 42   | 0.2216          | -0.4872 |
| 0.0726        | 4.0   | 56   | 0.1972          | -0.3234 |
| 0.0564        | 5.0   | 70   | 0.2832          | -0.9009 |
| 0.0525        | 6.0   | 84   | 0.1854          | -0.2444 |
| 0.0385        | 7.0   | 98   | 0.2816          | -0.8900 |
| 0.0257        | 8.0   | 112  | 0.1815          | -0.2183 |
| 0.03          | 9.0   | 126  | 0.3065          | -1.0576 |
| 0.0275        | 10.0  | 140  | 0.1991          | -0.3367 |
| 0.0175        | 11.0  | 154  | 0.2400          | -0.6110 |
| 0.017         | 12.0  | 168  | 0.1915          | -0.2856 |
| 0.0158        | 13.0  | 182  | 0.2008          | -0.3477 |
| 0.0127        | 14.0  | 196  | 0.1932          | -0.2968 |
| 0.009         | 15.0  | 210  | 0.2500          | -0.6783 |
| 0.0078        | 16.0  | 224  | 0.1969          | -0.3215 |
| 0.0075        | 17.0  | 238  | 0.1857          | -0.2463 |
| 0.0079        | 18.0  | 252  | 0.2405          | -0.6145 |
| 0.0089        | 19.0  | 266  | 0.1865          | -0.2517 |
| 0.0082        | 20.0  | 280  | 0.2275          | -0.5267 |
| 0.0078        | 21.0  | 294  | 0.1890          | -0.2687 |
| 0.0072        | 22.0  | 308  | 0.2230          | -0.4965 |
| 0.0064        | 23.0  | 322  | 0.2286          | -0.5346 |
| 0.0052        | 24.0  | 336  | 0.2154          | -0.4457 |
| 0.0049        | 25.0  | 350  | 0.1901          | -0.2757 |
| 0.0062        | 26.0  | 364  | 0.1917          | -0.2870 |
| 0.0043        | 27.0  | 378  | 0.2042          | -0.3704 |
| 0.0038        | 28.0  | 392  | 0.2251          | -0.5110 |
| 0.0049        | 29.0  | 406  | 0.2092          | -0.4040 |
| 0.0044        | 30.0  | 420  | 0.2119          | -0.4221 |
| 0.0041        | 31.0  | 434  | 0.2018          | -0.3542 |
| 0.0039        | 32.0  | 448  | 0.1875          | -0.2586 |
| 0.0038        | 33.0  | 462  | 0.1980          | -0.3291 |
| 0.0038        | 34.0  | 476  | 0.2071          | -0.3903 |
| 0.0043        | 35.0  | 490  | 0.1998          | -0.3412 |
| 0.0043        | 36.0  | 504  | 0.2052          | -0.3771 |
| 0.004         | 37.0  | 518  | 0.2143          | -0.4382 |
| 0.004         | 38.0  | 532  | 0.1977          | -0.3273 |
| 0.0039        | 39.0  | 546  | 0.2002          | -0.3439 |
| 0.0034        | 40.0  | 560  | 0.2035          | -0.3659 |
| 0.0036        | 41.0  | 574  | 0.1994          | -0.3387 |
| 0.0029        | 42.0  | 588  | 0.2036          | -0.3667 |
| 0.0032        | 43.0  | 602  | 0.2055          | -0.3797 |
| 0.0029        | 44.0  | 616  | 0.2025          | -0.3593 |
| 0.0027        | 45.0  | 630  | 0.2047          | -0.3743 |
| 0.0033        | 46.0  | 644  | 0.2067          | -0.3877 |
| 0.0027        | 47.0  | 658  | 0.2035          | -0.3662 |


### 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-concept", "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-concept
========================================


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: 0.2035
* R2: -0.3662


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