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# predict-perception-bertino-focus-victim

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: 0.2497
- R2: 0.6131

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5438        | 1.0   | 14   | 0.4405          | 0.3175 |
| 0.2336        | 2.0   | 28   | 0.2070          | 0.6792 |
| 0.0986        | 3.0   | 42   | 0.2868          | 0.5555 |
| 0.0907        | 4.0   | 56   | 0.2916          | 0.5481 |
| 0.0652        | 5.0   | 70   | 0.2187          | 0.6611 |
| 0.0591        | 6.0   | 84   | 0.2320          | 0.6406 |
| 0.0478        | 7.0   | 98   | 0.2501          | 0.6125 |
| 0.0347        | 8.0   | 112  | 0.2425          | 0.6243 |
| 0.021         | 9.0   | 126  | 0.2670          | 0.5863 |
| 0.0214        | 10.0  | 140  | 0.2853          | 0.5580 |
| 0.0172        | 11.0  | 154  | 0.2726          | 0.5776 |
| 0.0177        | 12.0  | 168  | 0.2629          | 0.5927 |
| 0.0152        | 13.0  | 182  | 0.2396          | 0.6287 |
| 0.012         | 14.0  | 196  | 0.2574          | 0.6012 |
| 0.0119        | 15.0  | 210  | 0.2396          | 0.6288 |
| 0.0128        | 16.0  | 224  | 0.2517          | 0.6100 |
| 0.0109        | 17.0  | 238  | 0.2509          | 0.6112 |
| 0.008         | 18.0  | 252  | 0.2522          | 0.6092 |
| 0.0101        | 19.0  | 266  | 0.2503          | 0.6121 |
| 0.0075        | 20.0  | 280  | 0.2527          | 0.6084 |
| 0.0082        | 21.0  | 294  | 0.2544          | 0.6058 |
| 0.0061        | 22.0  | 308  | 0.2510          | 0.6111 |
| 0.006         | 23.0  | 322  | 0.2402          | 0.6279 |
| 0.005         | 24.0  | 336  | 0.2539          | 0.6066 |
| 0.0058        | 25.0  | 350  | 0.2438          | 0.6222 |
| 0.0051        | 26.0  | 364  | 0.2439          | 0.6221 |
| 0.006         | 27.0  | 378  | 0.2442          | 0.6216 |
| 0.0061        | 28.0  | 392  | 0.2416          | 0.6257 |
| 0.0053        | 29.0  | 406  | 0.2519          | 0.6097 |
| 0.0045        | 30.0  | 420  | 0.2526          | 0.6085 |
| 0.0034        | 31.0  | 434  | 0.2578          | 0.6006 |
| 0.0039        | 32.0  | 448  | 0.2557          | 0.6038 |
| 0.0043        | 33.0  | 462  | 0.2538          | 0.6068 |
| 0.0041        | 34.0  | 476  | 0.2535          | 0.6072 |
| 0.0042        | 35.0  | 490  | 0.2560          | 0.6033 |
| 0.0037        | 36.0  | 504  | 0.2576          | 0.6009 |
| 0.0036        | 37.0  | 518  | 0.2634          | 0.5919 |
| 0.0037        | 38.0  | 532  | 0.2582          | 0.5999 |
| 0.0038        | 39.0  | 546  | 0.2552          | 0.6045 |
| 0.0034        | 40.0  | 560  | 0.2563          | 0.6028 |
| 0.0033        | 41.0  | 574  | 0.2510          | 0.6110 |
| 0.0029        | 42.0  | 588  | 0.2515          | 0.6103 |
| 0.0033        | 43.0  | 602  | 0.2525          | 0.6088 |
| 0.0028        | 44.0  | 616  | 0.2522          | 0.6093 |
| 0.0028        | 45.0  | 630  | 0.2526          | 0.6085 |
| 0.0027        | 46.0  | 644  | 0.2494          | 0.6136 |
| 0.0024        | 47.0  | 658  | 0.2497          | 0.6131 |


### 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-victim", "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-victim
=======================================


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: 0.2497
* R2: 0.6131


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