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# roberta-base-bne-finetuned_personality_multi_4

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: 4.1709
- Accuracy: 0.3470

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1759        | 1.0   | 125  | 2.1873          | 0.2548   |
| 1.8651        | 2.0   | 250  | 2.2285          | 0.2680   |
| 1.8619        | 3.0   | 375  | 2.1732          | 0.2951   |
| 1.7224        | 4.0   | 500  | 2.0688          | 0.3925   |
| 1.6432        | 5.0   | 625  | 2.1094          | 0.3735   |
| 1.3599        | 6.0   | 750  | 2.1732          | 0.3631   |
| 1.0623        | 7.0   | 875  | 2.4785          | 0.3579   |
| 1.0504        | 8.0   | 1000 | 2.4598          | 0.3844   |
| 0.7662        | 9.0   | 1125 | 2.8081          | 0.3573   |
| 0.9167        | 10.0  | 1250 | 2.9385          | 0.3452   |
| 0.6391        | 11.0  | 1375 | 2.9933          | 0.3320   |
| 0.3893        | 12.0  | 1500 | 3.1037          | 0.3579   |
| 0.673         | 13.0  | 1625 | 3.4369          | 0.3631   |
| 0.3498        | 14.0  | 1750 | 3.6396          | 0.3383   |
| 0.3891        | 15.0  | 1875 | 3.8332          | 0.3556   |
| 0.0818        | 16.0  | 2000 | 3.9451          | 0.3401   |
| 0.1438        | 17.0  | 2125 | 3.9271          | 0.3458   |
| 0.0634        | 18.0  | 2250 | 4.1564          | 0.3481   |
| 0.0121        | 19.0  | 2375 | 4.1405          | 0.3499   |
| 0.0071        | 20.0  | 2500 | 4.1709          | 0.3470   |


### Framework versions

- Transformers 4.19.4
- 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_4", "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\_4
=================================================


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: 4.1709
* Accuracy: 0.3470


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: 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 4.19.4
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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 4.19.4
* 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: 0.0001
* 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 4.19.4
* 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: 0.0001
* 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 4.19.4
* Pytorch 1.11.0+cu113
* Datasets 2.2.2
* Tokenizers 0.12.1