
<!-- 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-mrpc-target-glue-mnli

This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-mrpc](https://huggingface.co/muhtasham/tiny-mlm-glue-mrpc) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8094
- Accuracy: 0.6373

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0737        | 0.04  | 500   | 1.0366          | 0.4615   |
| 1.0169        | 0.08  | 1000  | 0.9833          | 0.5194   |
| 0.9799        | 0.12  | 1500  | 0.9344          | 0.5719   |
| 0.9452        | 0.16  | 2000  | 0.9106          | 0.5879   |
| 0.9293        | 0.2   | 2500  | 0.8905          | 0.5962   |
| 0.9189        | 0.24  | 3000  | 0.8801          | 0.6026   |
| 0.9017        | 0.29  | 3500  | 0.8705          | 0.6103   |
| 0.896         | 0.33  | 4000  | 0.8619          | 0.6178   |
| 0.881         | 0.37  | 4500  | 0.8574          | 0.6211   |
| 0.8854        | 0.41  | 5000  | 0.8495          | 0.6201   |
| 0.8756        | 0.45  | 5500  | 0.8434          | 0.6223   |
| 0.8713        | 0.49  | 6000  | 0.8410          | 0.6263   |
| 0.8757        | 0.53  | 6500  | 0.8337          | 0.6301   |
| 0.8624        | 0.57  | 7000  | 0.8363          | 0.6284   |
| 0.8576        | 0.61  | 7500  | 0.8203          | 0.6356   |
| 0.8583        | 0.65  | 8000  | 0.8188          | 0.6378   |
| 0.8523        | 0.69  | 8500  | 0.8294          | 0.6304   |
| 0.8533        | 0.73  | 9000  | 0.8052          | 0.6429   |
| 0.8448        | 0.77  | 9500  | 0.8180          | 0.6356   |
| 0.8368        | 0.81  | 10000 | 0.8030          | 0.6399   |
| 0.8389        | 0.86  | 10500 | 0.8094          | 0.6373   |


### 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-mrpc-target-glue-mnli", "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-mrpc-target-glue-mnli
===================================


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


* Loss: 0.8094
* Accuracy: 0.6373


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