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# roberta-base-bne-finetuned_personality_multi

This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3709
- Accuracy: 0.5130

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2576        | 1.0   | 125  | 2.2755          | 0.2340   |
| 2.0409        | 2.0   | 250  | 2.1425          | 0.2974   |
| 1.6358        | 3.0   | 375  | 1.8730          | 0.4403   |
| 1.3553        | 4.0   | 500  | 1.7443          | 0.5032   |
| 0.9201        | 5.0   | 625  | 1.7165          | 0.5055   |
| 0.5199        | 6.0   | 750  | 1.7476          | 0.5107   |
| 0.5588        | 7.0   | 875  | 1.7758          | 0.5153   |
| 0.2079        | 8.0   | 1000 | 1.7964          | 0.5251   |
| 0.2685        | 9.0   | 1125 | 1.8886          | 0.5187   |
| 0.1261        | 10.0  | 1250 | 1.9463          | 0.5199   |
| 0.1105        | 11.0  | 1375 | 2.0337          | 0.5222   |
| 0.1572        | 12.0  | 1500 | 2.1206          | 0.5084   |
| 0.0643        | 13.0  | 1625 | 2.1815          | 0.5182   |
| 0.0174        | 14.0  | 1750 | 2.2412          | 0.5176   |
| 0.0266        | 15.0  | 1875 | 2.2741          | 0.5112   |
| 0.0447        | 16.0  | 2000 | 2.3089          | 0.5159   |
| 0.02          | 17.0  | 2125 | 2.3401          | 0.5135   |
| 0.0414        | 18.0  | 2250 | 2.3504          | 0.5159   |
| 0.0122        | 19.0  | 2375 | 2.3661          | 0.5130   |
| 0.0154        | 20.0  | 2500 | 2.3709          | 0.5130   |


### Framework versions

- Transformers 4.19.3
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "roberta-base-bne-finetuned_personality_multi", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

roberta-base-bne-finetuned\_personality\_multi
==============================================


This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3709
* Accuracy: 0.5130


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: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.19.3
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1