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# tiny-mlm-glue-wnli-target-glue-qqp

This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-wnli](https://huggingface.co/muhtasham/tiny-mlm-glue-wnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4204
- Accuracy: 0.7892
- F1: 0.7460

## 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
- training_steps: 5000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5839        | 0.04  | 500  | 0.5193          | 0.7299   | 0.6543 |
| 0.5179        | 0.09  | 1000 | 0.4861          | 0.7508   | 0.6874 |
| 0.5047        | 0.13  | 1500 | 0.4916          | 0.7406   | 0.7097 |
| 0.4871        | 0.18  | 2000 | 0.4647          | 0.7584   | 0.7182 |
| 0.4789        | 0.22  | 2500 | 0.4564          | 0.7637   | 0.7240 |
| 0.4622        | 0.26  | 3000 | 0.4496          | 0.7668   | 0.7296 |
| 0.4617        | 0.31  | 3500 | 0.4468          | 0.7678   | 0.7343 |
| 0.454         | 0.35  | 4000 | 0.4415          | 0.7718   | 0.7376 |
| 0.4553        | 0.4   | 4500 | 0.4371          | 0.7755   | 0.7415 |
| 0.4438        | 0.44  | 5000 | 0.4204          | 0.7892   | 0.7460 |


### 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", "f1"], "model-index": [{"name": "tiny-mlm-glue-wnli-target-glue-qqp", "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-wnli-target-glue-qqp
==================================


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


* Loss: 0.4204
* Accuracy: 0.7892
* F1: 0.7460


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
* training\_steps: 5000


### 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
* training\_steps: 5000 ### 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
* training\_steps: 5000 ### 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
* training\_steps: 5000### Training results### Framework versions


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