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# DeBERTa v3 (small) fine-tuned on MRPC

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2787
- Accuracy: 0.8922
- F1: 0.9233
- Combined Score: 0.9078

## 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: 3e-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
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| No log        | 1.0   | 230  | 0.2787          | 0.8922   | 0.9233 | 0.9078         |
| No log        | 2.0   | 460  | 0.3651          | 0.875    | 0.9137 | 0.8944         |
| No log        | 3.0   | 690  | 0.5238          | 0.8799   | 0.9179 | 0.8989         |
| No log        | 4.0   | 920  | 0.4712          | 0.8946   | 0.9222 | 0.9084         |
| 0.2147        | 5.0   | 1150 | 0.5704          | 0.8946   | 0.9262 | 0.9104         |
| 0.2147        | 6.0   | 1380 | 0.5697          | 0.8995   | 0.9284 | 0.9140         |
| 0.2147        | 7.0   | 1610 | 0.6651          | 0.8922   | 0.9214 | 0.9068         |
| 0.2147        | 8.0   | 1840 | 0.6726          | 0.8946   | 0.9239 | 0.9093         |
| 0.0183        | 9.0   | 2070 | 0.7250          | 0.8848   | 0.9177 | 0.9012         |
| 0.0183        | 10.0  | 2300 | 0.7093          | 0.8922   | 0.9223 | 0.9072         |


### Framework versions

- Transformers 4.13.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3

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transformers pytorch tensorboard deberta-v2 text-classification generated_from_trainer deberta-v3 en dataset:glue license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #deberta-v2 #text-classification #generated_from_trainer #deberta-v3 #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

DeBERTa v3 (small) fine-tuned on MRPC
=====================================


This model is a fine-tuned version of microsoft/deberta-v3-small on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2787
* Accuracy: 0.8922
* F1: 0.9233
* Combined Score: 0.9078


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: 3e-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
* num\_epochs: 10.0


### Training results



### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-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
* num\_epochs: 10.0 ### Training results ### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #deberta-v2 #text-classification #generated_from_trainer #deberta-v3 #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-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
* num\_epochs: 10.0 ### Training results ### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #deberta-v2 #text-classification #generated_from_trainer #deberta-v3 #en #dataset-glue #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-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
* num\_epochs: 10.0### Training results### Framework versions


* Transformers 4.13.0.dev0
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3