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# legalbert-adept

This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6927

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 70.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.4774        | 1.0   | 907   | 4.6352          |
| 4.5985        | 2.0   | 1814  | 4.2252          |
| 4.2598        | 3.0   | 2721  | 3.9970          |
| 4.0564        | 4.0   | 3628  | 3.8458          |
| 3.852         | 5.0   | 4535  | 3.6996          |
| 3.7954        | 6.0   | 5442  | 3.5729          |
| 3.6572        | 7.0   | 6349  | 3.4669          |
| 3.5174        | 8.0   | 7256  | 3.3176          |
| 3.3779        | 9.0   | 8163  | 3.1742          |
| 3.2451        | 10.0  | 9070  | 3.1204          |
| 3.1785        | 11.0  | 9977  | 3.0070          |
| 3.0627        | 12.0  | 10884 | 2.9171          |
| 2.9859        | 13.0  | 11791 | 2.8068          |
| 2.8921        | 14.0  | 12698 | 2.7104          |
| 2.7894        | 15.0  | 13605 | 2.6986          |
| 2.754         | 16.0  | 14512 | 2.6349          |
| 2.6242        | 17.0  | 15419 | 2.5321          |
| 2.6069        | 18.0  | 16326 | 2.5110          |
| 2.5147        | 19.0  | 17233 | 2.4618          |
| 2.4694        | 20.0  | 18140 | 2.3947          |
| 2.4267        | 21.0  | 19047 | 2.3827          |
| 2.3936        | 22.0  | 19954 | 2.3171          |
| 2.3613        | 23.0  | 20861 | 2.2848          |
| 2.2855        | 24.0  | 21768 | 2.2050          |
| 2.2256        | 25.0  | 22675 | 2.1967          |
| 2.2242        | 26.0  | 23582 | 2.1683          |
| 2.1924        | 27.0  | 24489 | 2.1475          |
| 2.136         | 28.0  | 25396 | 2.1203          |
| 2.0947        | 29.0  | 26303 | 2.0854          |
| 2.1093        | 30.0  | 27210 | 2.0813          |
| 2.0255        | 31.0  | 28117 | 2.0102          |
| 1.9977        | 32.0  | 29024 | 2.0168          |
| 1.9815        | 33.0  | 29931 | 2.0015          |
| 1.9804        | 34.0  | 30838 | 1.9795          |
| 1.9459        | 35.0  | 31745 | 1.9581          |
| 1.9032        | 36.0  | 32652 | 1.9227          |
| 1.8959        | 37.0  | 33559 | 1.9146          |
| 1.9449        | 38.0  | 34466 | 1.8836          |
| 1.8673        | 39.0  | 35373 | 1.9147          |
| 1.8379        | 40.0  | 36280 | 1.9020          |
| 1.8424        | 41.0  | 37187 | 1.8786          |
| 1.8173        | 42.0  | 38094 | 1.8736          |
| 1.8092        | 43.0  | 39001 | 1.8398          |
| 1.7937        | 44.0  | 39908 | 1.8393          |
| 1.7844        | 45.0  | 40815 | 1.7940          |
| 1.7868        | 46.0  | 41722 | 1.8064          |
| 1.7554        | 47.0  | 42629 | 1.7834          |
| 1.7161        | 48.0  | 43536 | 1.7966          |
| 1.7715        | 49.0  | 44443 | 1.8080          |
| 1.7177        | 50.0  | 45350 | 1.7561          |
| 1.6985        | 51.0  | 46257 | 1.7451          |
| 1.7119        | 52.0  | 47164 | 1.7476          |
| 1.6712        | 53.0  | 48071 | 1.7359          |
| 1.6765        | 54.0  | 48978 | 1.7663          |
| 1.6749        | 55.0  | 49885 | 1.7227          |
| 1.6639        | 56.0  | 50792 | 1.7032          |
| 1.6363        | 57.0  | 51699 | 1.7090          |
| 1.6378        | 58.0  | 52606 | 1.7037          |
| 1.6237        | 59.0  | 53513 | 1.7047          |
| 1.6311        | 60.0  | 54420 | 1.7031          |
| 1.592         | 61.0  | 55327 | 1.7099          |
| 1.6111        | 62.0  | 56234 | 1.6824          |
| 1.6026        | 63.0  | 57141 | 1.6669          |
| 1.6252        | 64.0  | 58048 | 1.6886          |
| 1.6184        | 65.0  | 58955 | 1.6742          |
| 1.6088        | 66.0  | 59862 | 1.7186          |
| 1.6246        | 67.0  | 60769 | 1.6937          |
| 1.5948        | 68.0  | 61676 | 1.6868          |
| 1.5951        | 69.0  | 62583 | 1.7186          |
| 1.5775        | 70.0  | 63490 | 1.6775          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1

{"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "legalbert-adept", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 

legalbert-adept
===============


This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.6927


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 500
* num\_epochs: 70.0### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.11.0
* Datasets 2.1.0
* Tokenizers 0.12.1