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# predict-perception-bertino-focus-assassin

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: 0.3409
- R2: 0.3205

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5573        | 1.0   | 14   | 0.4856          | 0.0321 |
| 0.1739        | 2.0   | 28   | 0.4735          | 0.0562 |
| 0.0813        | 3.0   | 42   | 0.3416          | 0.3191 |
| 0.0764        | 4.0   | 56   | 0.3613          | 0.2799 |
| 0.0516        | 5.0   | 70   | 0.3264          | 0.3495 |
| 0.0459        | 6.0   | 84   | 0.4193          | 0.1643 |
| 0.0414        | 7.0   | 98   | 0.3502          | 0.3019 |
| 0.028         | 8.0   | 112  | 0.3361          | 0.3301 |
| 0.0281        | 9.0   | 126  | 0.3610          | 0.2804 |
| 0.027         | 10.0  | 140  | 0.3523          | 0.2978 |
| 0.0216        | 11.0  | 154  | 0.3440          | 0.3143 |
| 0.0181        | 12.0  | 168  | 0.3506          | 0.3012 |
| 0.013         | 13.0  | 182  | 0.3299          | 0.3424 |
| 0.0116        | 14.0  | 196  | 0.3611          | 0.2803 |
| 0.0118        | 15.0  | 210  | 0.3505          | 0.3013 |
| 0.0139        | 16.0  | 224  | 0.3529          | 0.2967 |
| 0.0099        | 17.0  | 238  | 0.3536          | 0.2952 |
| 0.0096        | 18.0  | 252  | 0.3542          | 0.2941 |
| 0.0107        | 19.0  | 266  | 0.3770          | 0.2486 |
| 0.0088        | 20.0  | 280  | 0.3467          | 0.3091 |
| 0.0065        | 21.0  | 294  | 0.3327          | 0.3369 |
| 0.0073        | 22.0  | 308  | 0.3479          | 0.3066 |
| 0.0062        | 23.0  | 322  | 0.3566          | 0.2893 |
| 0.0063        | 24.0  | 336  | 0.3503          | 0.3019 |
| 0.0057        | 25.0  | 350  | 0.3371          | 0.3282 |
| 0.0049        | 26.0  | 364  | 0.3334          | 0.3355 |
| 0.0045        | 27.0  | 378  | 0.3399          | 0.3225 |
| 0.0049        | 28.0  | 392  | 0.3379          | 0.3266 |
| 0.0049        | 29.0  | 406  | 0.3377          | 0.3268 |
| 0.0055        | 30.0  | 420  | 0.3357          | 0.3309 |
| 0.005         | 31.0  | 434  | 0.3394          | 0.3235 |
| 0.0046        | 32.0  | 448  | 0.3432          | 0.3159 |
| 0.0048        | 33.0  | 462  | 0.3427          | 0.3169 |
| 0.0041        | 34.0  | 476  | 0.3450          | 0.3123 |
| 0.0041        | 35.0  | 490  | 0.3436          | 0.3151 |
| 0.0051        | 36.0  | 504  | 0.3394          | 0.3234 |
| 0.0037        | 37.0  | 518  | 0.3370          | 0.3283 |
| 0.004         | 38.0  | 532  | 0.3370          | 0.3284 |
| 0.0033        | 39.0  | 546  | 0.3339          | 0.3344 |
| 0.0034        | 40.0  | 560  | 0.3335          | 0.3352 |
| 0.003         | 41.0  | 574  | 0.3373          | 0.3276 |
| 0.0035        | 42.0  | 588  | 0.3380          | 0.3264 |
| 0.0032        | 43.0  | 602  | 0.3382          | 0.3259 |
| 0.0034        | 44.0  | 616  | 0.3432          | 0.3158 |
| 0.003         | 45.0  | 630  | 0.3421          | 0.3181 |
| 0.0027        | 46.0  | 644  | 0.3410          | 0.3203 |
| 0.0037        | 47.0  | 658  | 0.3409          | 0.3205 |


### 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-assassin", "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-assassin
=========================================


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: 0.3409
* R2: 0.3205


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