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# roberta-base-qqp

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4435
- Accuracy: 0.9153
- F1: 0.8867
- Combined Score: 0.9010

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|:--------------:|
| 0.2751        | 1.0   | 22741  | 0.3057          | 0.8905   | 0.8512 | 0.8709         |
| 0.2443        | 2.0   | 45482  | 0.2530          | 0.9005   | 0.8710 | 0.8857         |
| 0.2157        | 3.0   | 68223  | 0.2643          | 0.9070   | 0.8769 | 0.8919         |
| 0.1838        | 4.0   | 90964  | 0.2806          | 0.9109   | 0.8815 | 0.8962         |
| 0.146         | 5.0   | 113705 | 0.3277          | 0.9113   | 0.8809 | 0.8961         |
| 0.1262        | 6.0   | 136446 | 0.3939          | 0.9113   | 0.8812 | 0.8962         |
| 0.0867        | 7.0   | 159187 | 0.4435          | 0.9153   | 0.8867 | 0.9010         |
| 0.0757        | 8.0   | 181928 | 0.4812          | 0.9147   | 0.8844 | 0.8996         |
| 0.0479        | 9.0   | 204669 | 0.5081          | 0.9151   | 0.8871 | 0.9011         |
| 0.0379        | 10.0  | 227410 | 0.5647          | 0.9149   | 0.8858 | 0.9003         |


### Framework versions

- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1

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transformers pytorch tensorboard roberta text-classification generated_from_trainer en dataset:glue license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

roberta-base-qqp
================


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


* Loss: 0.4435
* Accuracy: 0.9153
* F1: 0.8867
* Combined Score: 0.9010


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: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 10.0


### Training results



### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 10.0 ### Training results ### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #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: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 10.0 ### Training results ### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #roberta #text-classification #generated_from_trainer #en #dataset-glue #license-mit #model-index #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: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.06
* num\_epochs: 10.0### Training results### Framework versions


* Transformers 4.20.0.dev0
* Pytorch 1.11.0+cu113
* Datasets 2.1.0
* Tokenizers 0.12.1