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# predict-perception-bertino-cause-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: 0.0766
- R2: 0.8216

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6807        | 1.0   | 14   | 0.4011          | 0.0652 |
| 0.3529        | 2.0   | 28   | 0.2304          | 0.4631 |
| 0.1539        | 3.0   | 42   | 0.0596          | 0.8611 |
| 0.0853        | 4.0   | 56   | 0.1600          | 0.6272 |
| 0.066         | 5.0   | 70   | 0.1596          | 0.6280 |
| 0.0563        | 6.0   | 84   | 0.1146          | 0.7330 |
| 0.0777        | 7.0   | 98   | 0.1010          | 0.7646 |
| 0.0299        | 8.0   | 112  | 0.0897          | 0.7910 |
| 0.0311        | 9.0   | 126  | 0.0832          | 0.8061 |
| 0.0274        | 10.0  | 140  | 0.0988          | 0.7697 |
| 0.0262        | 11.0  | 154  | 0.1048          | 0.7557 |
| 0.0204        | 12.0  | 168  | 0.0615          | 0.8566 |
| 0.0254        | 13.0  | 182  | 0.0742          | 0.8270 |
| 0.0251        | 14.0  | 196  | 0.0923          | 0.7850 |
| 0.0149        | 15.0  | 210  | 0.0663          | 0.8456 |
| 0.0141        | 16.0  | 224  | 0.0755          | 0.8241 |
| 0.0112        | 17.0  | 238  | 0.0905          | 0.7891 |
| 0.0108        | 18.0  | 252  | 0.0834          | 0.8057 |
| 0.0096        | 19.0  | 266  | 0.0823          | 0.8082 |
| 0.0073        | 20.0  | 280  | 0.0825          | 0.8078 |
| 0.0092        | 21.0  | 294  | 0.0869          | 0.7974 |
| 0.0075        | 22.0  | 308  | 0.0744          | 0.8266 |
| 0.0075        | 23.0  | 322  | 0.0825          | 0.8078 |
| 0.0062        | 24.0  | 336  | 0.0797          | 0.8144 |
| 0.0065        | 25.0  | 350  | 0.0793          | 0.8152 |
| 0.007         | 26.0  | 364  | 0.0840          | 0.8043 |
| 0.0067        | 27.0  | 378  | 0.0964          | 0.7753 |
| 0.0064        | 28.0  | 392  | 0.0869          | 0.7976 |
| 0.0063        | 29.0  | 406  | 0.0766          | 0.8215 |
| 0.0057        | 30.0  | 420  | 0.0764          | 0.8219 |
| 0.0057        | 31.0  | 434  | 0.0796          | 0.8145 |
| 0.0054        | 32.0  | 448  | 0.0853          | 0.8012 |
| 0.0044        | 33.0  | 462  | 0.0750          | 0.8253 |
| 0.0072        | 34.0  | 476  | 0.0782          | 0.8179 |
| 0.006         | 35.0  | 490  | 0.0867          | 0.7979 |
| 0.0054        | 36.0  | 504  | 0.0819          | 0.8092 |
| 0.0047        | 37.0  | 518  | 0.0839          | 0.8045 |
| 0.0043        | 38.0  | 532  | 0.0764          | 0.8221 |
| 0.0039        | 39.0  | 546  | 0.0728          | 0.8303 |
| 0.0041        | 40.0  | 560  | 0.0755          | 0.8241 |
| 0.0038        | 41.0  | 574  | 0.0729          | 0.8301 |
| 0.0034        | 42.0  | 588  | 0.0781          | 0.8180 |
| 0.0038        | 43.0  | 602  | 0.0762          | 0.8224 |
| 0.0032        | 44.0  | 616  | 0.0777          | 0.8189 |
| 0.0035        | 45.0  | 630  | 0.0776          | 0.8191 |
| 0.0037        | 46.0  | 644  | 0.0765          | 0.8217 |
| 0.0036        | 47.0  | 658  | 0.0766          | 0.8216 |


### 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-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-cause-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: 0.0766
* R2: 0.8216


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