
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# roberta-base-finetuned-cvbest2

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1263
- Precision: 0.6839
- Recall: 0.7805
- F1: 0.7290
- Accuracy: 0.9674

## 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: 5e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 17   | 0.4054          | 0.5       | 0.0010 | 0.0019 | 0.9038   |
| No log        | 2.0   | 34   | 0.2859          | 0.3247    | 0.2660 | 0.2924 | 0.9201   |
| No log        | 3.0   | 51   | 0.2169          | 0.3832    | 0.5774 | 0.4606 | 0.9358   |
| No log        | 4.0   | 68   | 0.1691          | 0.4744    | 0.6634 | 0.5532 | 0.9504   |
| No log        | 5.0   | 85   | 0.1571          | 0.5145    | 0.7360 | 0.6057 | 0.9495   |
| No log        | 6.0   | 102  | 0.1458          | 0.5905    | 0.7669 | 0.6672 | 0.9596   |
| No log        | 7.0   | 119  | 0.1304          | 0.6293    | 0.7718 | 0.6933 | 0.9630   |
| No log        | 8.0   | 136  | 0.1284          | 0.6664    | 0.7901 | 0.7230 | 0.9666   |
| No log        | 9.0   | 153  | 0.1263          | 0.6839    | 0.7805 | 0.7290 | 0.9674   |
| No log        | 10.0  | 170  | 0.1295          | 0.6699    | 0.7930 | 0.7263 | 0.9669   |


### Framework versions

- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "roberta-base-finetuned-cvbest2", "results": []}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

roberta-base-finetuned-cvbest2
==============================


This model is a fine-tuned version of roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1263
* Precision: 0.6839
* Recall: 0.7805
* F1: 0.7290
* Accuracy: 0.9674


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: 5e-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: 10


### Training results



### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 10 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 10 ### Training results ### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #roberta #token-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 10### Training results### Framework versions


* Transformers 4.27.1
* Pytorch 1.13.1+cu116
* Datasets 2.10.1
* Tokenizers 0.13.2