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# roberta-base-bne-finetuned_personality_multi_3

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: 2.1145
- Accuracy: 0.4847

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2498        | 1.0   | 63   | 2.2799          | 0.2236   |
| 2.3044        | 2.0   | 126  | 2.1644          | 0.2980   |
| 1.9017        | 3.0   | 189  | 1.9934          | 0.4127   |
| 2.2281        | 4.0   | 252  | 1.8517          | 0.4501   |
| 1.2955        | 5.0   | 315  | 1.7588          | 0.4870   |
| 1.221         | 6.0   | 378  | 1.7269          | 0.4888   |
| 1.1381        | 7.0   | 441  | 1.7617          | 0.4888   |
| 0.8415        | 8.0   | 504  | 1.8101          | 0.4853   |
| 0.6696        | 9.0   | 567  | 1.8325          | 0.4928   |
| 0.6646        | 10.0  | 630  | 1.8707          | 0.4841   |
| 0.3758        | 11.0  | 693  | 1.8766          | 0.4876   |
| 0.3477        | 12.0  | 756  | 1.9171          | 0.4905   |
| 0.2854        | 13.0  | 819  | 1.9203          | 0.4980   |
| 0.2713        | 14.0  | 882  | 2.0089          | 0.4813   |
| 0.3434        | 15.0  | 945  | 2.0130          | 0.4905   |
| 0.0758        | 16.0  | 1008 | 2.0230          | 0.4922   |
| 0.2518        | 17.0  | 1071 | 2.0793          | 0.4824   |
| 0.0783        | 18.0  | 1134 | 2.0920          | 0.4830   |
| 0.0933        | 19.0  | 1197 | 2.1067          | 0.4836   |
| 0.184         | 20.0  | 1260 | 2.1145          | 0.4847   |


### 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_3", "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\_3
=================================================


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: 2.1145
* Accuracy: 0.4847


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: 32
* eval\_batch\_size: 32
* 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: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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: 1e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* 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