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# tiny-mlm-glue-qnli-target-glue-sst2

This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-qnli](https://huggingface.co/muhtasham/tiny-mlm-glue-qnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5008
- Accuracy: 0.8211

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5757        | 0.24  | 500  | 0.4901          | 0.7775   |
| 0.4436        | 0.48  | 1000 | 0.4673          | 0.7833   |
| 0.3947        | 0.71  | 1500 | 0.4434          | 0.7970   |
| 0.3751        | 0.95  | 2000 | 0.4601          | 0.7970   |
| 0.3326        | 1.19  | 2500 | 0.4463          | 0.8005   |
| 0.316         | 1.43  | 3000 | 0.4510          | 0.8005   |
| 0.2981        | 1.66  | 3500 | 0.4367          | 0.8142   |
| 0.2929        | 1.9   | 4000 | 0.4383          | 0.8108   |
| 0.2746        | 2.14  | 4500 | 0.4873          | 0.8016   |
| 0.256         | 2.38  | 5000 | 0.4395          | 0.8165   |
| 0.246         | 2.61  | 5500 | 0.4444          | 0.8280   |
| 0.2522        | 2.85  | 6000 | 0.4478          | 0.8245   |
| 0.2371        | 3.09  | 6500 | 0.4556          | 0.8291   |
| 0.2299        | 3.33  | 7000 | 0.4655          | 0.8326   |
| 0.2143        | 3.56  | 7500 | 0.4581          | 0.8314   |
| 0.2153        | 3.8   | 8000 | 0.4869          | 0.8291   |
| 0.2134        | 4.04  | 8500 | 0.5008          | 0.8211   |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "tiny-mlm-glue-qnli-target-glue-sst2", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

tiny-mlm-glue-qnli-target-glue-sst2
===================================


This model is a fine-tuned version of muhtasham/tiny-mlm-glue-qnli on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5008
* Accuracy: 0.8211


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 200


### Training results



### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.0+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 3e-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: constant
* num\_epochs: 200 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.0+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #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: 3e-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: constant
* num\_epochs: 200 ### Training results ### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.0+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #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: 3e-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: constant
* num\_epochs: 200### Training results### Framework versions


* Transformers 4.26.0.dev0
* Pytorch 1.13.0+cu116
* Datasets 2.8.1.dev0
* Tokenizers 0.13.2