
<!-- 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. -->

# kaz_legal_bert_5_6

This model is a fine-tuned version of [kaisar-barlybay-sse/kaz_legal_bert_5](https://huggingface.co/kaisar-barlybay-sse/kaz_legal_bert_5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3860
- Accuracy: 0.3273

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3921        | 1.0   | 501  | 1.3862          | 0.3074   |
| 1.3945        | 2.0   | 1002 | 1.3860          | 0.3293   |
| 1.3914        | 3.0   | 1503 | 1.3863          | 0.3094   |
| 1.3972        | 4.0   | 2004 | 1.3862          | 0.3214   |
| 1.3969        | 5.0   | 2505 | 1.3862          | 0.3273   |
| 1.3944        | 6.0   | 3006 | 1.3860          | 0.3273   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "kaz_legal_bert_5_6", "results": []}]}
transformers pytorch tensorboard bert multiple-choice generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #multiple-choice #generated_from_trainer #endpoints_compatible #region-us 

kaz\_legal\_bert\_5\_6
======================


This model is a fine-tuned version of kaisar-barlybay-sse/kaz\_legal\_bert\_5 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.3860
* Accuracy: 0.3273


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: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #bert #multiple-choice #generated_from_trainer #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 6 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.11.0
* Tokenizers 0.13.3