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# K-12BERT-reward-neurallinguisticpioneers

This model is a fine-tuned version of [vasugoel/K-12BERT](https://huggingface.co/vasugoel/K-12BERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2926

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0129        | 1.0   | 244  | 0.4501          |
| 0.5275        | 2.0   | 488  | 0.5272          |
| 0.3624        | 3.0   | 732  | 0.3435          |
| 0.3053        | 4.0   | 976  | 0.2740          |
| 0.2485        | 5.0   | 1220 | 0.2465          |
| 0.2157        | 6.0   | 1464 | 0.2992          |
| 0.1942        | 7.0   | 1708 | 0.2495          |
| 0.1751        | 8.0   | 1952 | 0.2605          |
| 0.175         | 9.0   | 2196 | 0.2192          |
| 0.1553        | 10.0  | 2440 | 0.2790          |
| 0.1449        | 11.0  | 2684 | 0.2566          |
| 0.1472        | 12.0  | 2928 | 0.2547          |
| 0.1443        | 13.0  | 3172 | 0.2600          |
| 0.1375        | 14.0  | 3416 | 0.3310          |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "K-12BERT-reward-neurallinguisticpioneers", "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 

K-12BERT-reward-neurallinguisticpioneers
========================================


This model is a fine-tuned version of vasugoel/K-12BERT on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.2926


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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 30


### Training results



### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: constant
* num\_epochs: 30 ### Training results ### Framework versions


* Transformers 4.27.3
* Pytorch 1.13.0+cu117
* Datasets 2.12.0
* Tokenizers 0.13.3