
<!-- 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. -->

# tiny-mlm-glue-cola-target-glue-qqp

This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-cola](https://huggingface.co/muhtasham/tiny-mlm-glue-cola) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4140
- Accuracy: 0.7961
- F1: 0.7697

## 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 | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.577         | 0.04  | 500   | 0.5181          | 0.7291   | 0.6837 |
| 0.5091        | 0.09  | 1000  | 0.4833          | 0.7514   | 0.7040 |
| 0.4964        | 0.13  | 1500  | 0.4910          | 0.7406   | 0.7144 |
| 0.4802        | 0.18  | 2000  | 0.4696          | 0.7531   | 0.7215 |
| 0.4728        | 0.22  | 2500  | 0.4583          | 0.7611   | 0.7271 |
| 0.4564        | 0.26  | 3000  | 0.4486          | 0.7685   | 0.7345 |
| 0.4575        | 0.31  | 3500  | 0.4472          | 0.7684   | 0.7371 |
| 0.4509        | 0.35  | 4000  | 0.4492          | 0.7663   | 0.7387 |
| 0.4511        | 0.4   | 4500  | 0.4417          | 0.7714   | 0.7430 |
| 0.4414        | 0.44  | 5000  | 0.4206          | 0.7894   | 0.7496 |
| 0.4295        | 0.48  | 5500  | 0.4274          | 0.7840   | 0.7511 |
| 0.4299        | 0.53  | 6000  | 0.4077          | 0.8008   | 0.7573 |
| 0.425         | 0.57  | 6500  | 0.4201          | 0.7908   | 0.7569 |
| 0.4259        | 0.62  | 7000  | 0.4052          | 0.8015   | 0.7594 |
| 0.4169        | 0.66  | 7500  | 0.4056          | 0.8046   | 0.7649 |
| 0.4305        | 0.7   | 8000  | 0.4115          | 0.7964   | 0.7619 |
| 0.4205        | 0.75  | 8500  | 0.3985          | 0.8054   | 0.7662 |
| 0.4152        | 0.79  | 9000  | 0.4183          | 0.7902   | 0.7618 |
| 0.4116        | 0.84  | 9500  | 0.3910          | 0.8103   | 0.7677 |
| 0.4136        | 0.88  | 10000 | 0.3874          | 0.8141   | 0.7710 |
| 0.4089        | 0.92  | 10500 | 0.3835          | 0.8155   | 0.7704 |
| 0.4085        | 0.97  | 11000 | 0.3847          | 0.8165   | 0.7718 |
| 0.4064        | 1.01  | 11500 | 0.4045          | 0.8005   | 0.7689 |
| 0.3857        | 1.06  | 12000 | 0.3823          | 0.8172   | 0.7746 |
| 0.3952        | 1.1   | 12500 | 0.3841          | 0.8144   | 0.7762 |
| 0.383         | 1.14  | 13000 | 0.3898          | 0.8124   | 0.7753 |
| 0.3724        | 1.19  | 13500 | 0.4140          | 0.7961   | 0.7697 |


### 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-cola-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-cola-target-glue-qqp
==================================


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


* Loss: 0.4140
* Accuracy: 0.7961
* F1: 0.7697


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