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# testing

This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5427
- Accuracy: 0.7455

## 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: 2e-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: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 47   | 0.6397          | 0.6364   |
| No log        | 2.0   | 94   | 0.6157          | 0.6788   |
| No log        | 3.0   | 141  | 0.5956          | 0.6788   |
| No log        | 4.0   | 188  | 0.5866          | 0.6848   |
| No log        | 5.0   | 235  | 0.5727          | 0.6788   |
| No log        | 6.0   | 282  | 0.5663          | 0.6970   |
| No log        | 7.0   | 329  | 0.5610          | 0.7091   |
| No log        | 8.0   | 376  | 0.5548          | 0.7091   |
| No log        | 9.0   | 423  | 0.5536          | 0.7212   |
| No log        | 10.0  | 470  | 0.5486          | 0.7273   |
| 0.583         | 11.0  | 517  | 0.5451          | 0.7273   |
| 0.583         | 12.0  | 564  | 0.5468          | 0.7333   |
| 0.583         | 13.0  | 611  | 0.5423          | 0.7394   |
| 0.583         | 14.0  | 658  | 0.5396          | 0.7394   |
| 0.583         | 15.0  | 705  | 0.5466          | 0.7394   |
| 0.583         | 16.0  | 752  | 0.5411          | 0.7455   |
| 0.583         | 17.0  | 799  | 0.5427          | 0.7455   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "testing", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 

testing
=======


This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.5427
* Accuracy: 0.7455


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: 2e-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: linear
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #license-mit #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-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: linear
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3