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# kaz_legal_distilbert_full_corpus_10.0

This model is a fine-tuned version of [S:\src\pipelines\distil_bert\models\3-epochs-full\model\checkpoint-11000](https://huggingface.co/S:\src\pipelines\distil_bert\models\3-epochs-full\model\checkpoint-11000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9163

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.6228        | 0.32  | 1000  | 6.4585          |
| 6.2811        | 0.64  | 2000  | 6.2602          |
| 6.1313        | 0.96  | 3000  | 6.1338          |
| 5.9671        | 1.28  | 4000  | 5.9722          |
| 5.8529        | 1.6   | 5000  | 5.8634          |
| 5.7655        | 1.92  | 6000  | 5.7714          |
| 5.6925        | 2.24  | 7000  | 5.6978          |
| 5.6311        | 2.56  | 8000  | 5.6411          |
| 5.5994        | 2.88  | 9000  | 5.6108          |
| 5.5758        | 3.2   | 10000 | 5.5260          |
| 5.4439        | 3.52  | 11000 | 5.3753          |
| 5.3187        | 3.84  | 12000 | 5.2224          |
| 5.0263        | 5.12  | 16000 | 4.7246          |
| 4.6228        | 6.4   | 20000 | 4.3538          |
| 4.31          | 7.68  | 24000 | 4.0828          |
| 4.1015        | 8.96  | 28000 | 3.9163          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "kaz_legal_distilbert_full_corpus_10.0", "results": []}]}
transformers pytorch distilbert fill-mask generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #fill-mask #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 

kaz\_legal\_distilbert\_full\_corpus\_10.0
==========================================


This model is a fine-tuned version of S:\src\pipelines\distil\_bert\models\3-epochs-full\model\checkpoint-11000 on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 3.9163


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
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* 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
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #distilbert #fill-mask #generated_from_trainer #autotrain_compatible #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
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3