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# tiny-mlm-glue-mnli-target-glue-mnli

This model is a fine-tuned version of [muhtasham/tiny-mlm-glue-mnli](https://huggingface.co/muhtasham/tiny-mlm-glue-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8010
- Accuracy: 0.6426

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0743        | 0.04  | 500   | 1.0281          | 0.4738   |
| 1.0045        | 0.08  | 1000  | 0.9576          | 0.5522   |
| 0.9565        | 0.12  | 1500  | 0.9155          | 0.5802   |
| 0.929         | 0.16  | 2000  | 0.8997          | 0.5936   |
| 0.9205        | 0.2   | 2500  | 0.8868          | 0.6011   |
| 0.9127        | 0.24  | 3000  | 0.8733          | 0.6066   |
| 0.8972        | 0.29  | 3500  | 0.8659          | 0.6121   |
| 0.8908        | 0.33  | 4000  | 0.8527          | 0.6202   |
| 0.8747        | 0.37  | 4500  | 0.8507          | 0.6200   |
| 0.8778        | 0.41  | 5000  | 0.8418          | 0.6254   |
| 0.869         | 0.45  | 5500  | 0.8373          | 0.6262   |
| 0.8647        | 0.49  | 6000  | 0.8339          | 0.6318   |
| 0.8677        | 0.53  | 6500  | 0.8268          | 0.6310   |
| 0.8576        | 0.57  | 7000  | 0.8269          | 0.6323   |
| 0.852         | 0.61  | 7500  | 0.8126          | 0.6396   |
| 0.8525        | 0.65  | 8000  | 0.8119          | 0.6399   |
| 0.8441        | 0.69  | 8500  | 0.8230          | 0.6319   |
| 0.8492        | 0.73  | 9000  | 0.7975          | 0.6486   |
| 0.8394        | 0.77  | 9500  | 0.8088          | 0.6373   |
| 0.8294        | 0.81  | 10000 | 0.7949          | 0.6460   |
| 0.8341        | 0.86  | 10500 | 0.8010          | 0.6426   |


### 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-mnli-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-mnli-target-glue-mnli
===================================


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


* Loss: 0.8010
* Accuracy: 0.6426


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