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# roberta-base_fold_1_binary_v1

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4984
- F1: 0.8339

## 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: 2e-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: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 288  | 0.3819          | 0.8117 |
| 0.4108        | 2.0   | 576  | 0.3696          | 0.8281 |
| 0.4108        | 3.0   | 864  | 0.4890          | 0.8343 |
| 0.2261        | 4.0   | 1152 | 0.7605          | 0.8298 |
| 0.2261        | 5.0   | 1440 | 0.7754          | 0.8307 |
| 0.1404        | 6.0   | 1728 | 0.7650          | 0.8174 |
| 0.0962        | 7.0   | 2016 | 0.8539          | 0.8315 |
| 0.0962        | 8.0   | 2304 | 1.0770          | 0.8263 |
| 0.0433        | 9.0   | 2592 | 1.1450          | 0.8292 |
| 0.0433        | 10.0  | 2880 | 1.1700          | 0.8205 |
| 0.0344        | 11.0  | 3168 | 1.2376          | 0.8241 |
| 0.0344        | 12.0  | 3456 | 1.2688          | 0.8329 |
| 0.0219        | 13.0  | 3744 | 1.3276          | 0.8283 |
| 0.0123        | 14.0  | 4032 | 1.2930          | 0.8320 |
| 0.0123        | 15.0  | 4320 | 1.4631          | 0.8266 |
| 0.0177        | 16.0  | 4608 | 1.4326          | 0.8270 |
| 0.0177        | 17.0  | 4896 | 1.4770          | 0.8334 |
| 0.0053        | 18.0  | 5184 | 1.5972          | 0.8214 |
| 0.0053        | 19.0  | 5472 | 1.5331          | 0.8327 |
| 0.0045        | 20.0  | 5760 | 1.5487          | 0.8359 |
| 0.0086        | 21.0  | 6048 | 1.4610          | 0.8315 |
| 0.0086        | 22.0  | 6336 | 1.4685          | 0.8353 |
| 0.0071        | 23.0  | 6624 | 1.4933          | 0.8358 |
| 0.0071        | 24.0  | 6912 | 1.4898          | 0.8310 |
| 0.0022        | 25.0  | 7200 | 1.4984          | 0.8339 |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "model-index": [{"name": "roberta-base_fold_1_binary_v1", "results": []}]}
transformers pytorch tensorboard roberta text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-base\_fold\_1\_binary\_v1
=================================


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


* Loss: 1.4984
* F1: 0.8339


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: 2e-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: 25


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 25 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 25 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: 25### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.0+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1