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# bert_uncased_L-4_H-512_A-8-finetuned-legal-definitions-longer

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the legal-definitions dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3701

## 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: 64
- eval_batch_size: 8
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4867        | 1.0   | 801  | 1.4951          |
| 1.429         | 2.0   | 1602 | 1.4872          |
| 1.4055        | 3.0   | 2403 | 1.4147          |
| 1.3703        | 4.0   | 3204 | 1.4231          |
| 1.3414        | 5.0   | 4005 | 1.4094          |
| 1.3254        | 6.0   | 4806 | 1.3913          |
| 1.3064        | 7.0   | 5607 | 1.3827          |
| 1.2967        | 8.0   | 6408 | 1.3905          |
| 1.2961        | 9.0   | 7209 | 1.3719          |
| 1.2824        | 10.0  | 8010 | 1.3701          |


### Framework versions

- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["finiteautomata/legal-definitions"], "base_model": "google/bert_uncased_L-4_H-512_A-8", "model-index": [{"name": "bert_uncased_L-4_H-512_A-8-finetuned-legal-definitions-longer", "results": []}]}
transformers pytorch tensorboard safetensors bert fill-mask generated_from_trainer dataset:finiteautomata/legal-definitions base_model:google/bert_uncased_L-4_H-512_A-8 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #fill-mask #generated_from_trainer #dataset-finiteautomata/legal-definitions #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert\_uncased\_L-4\_H-512\_A-8-finetuned-legal-definitions-longer
=================================================================


This model is a fine-tuned version of google/bert\_uncased\_L-4\_H-512\_A-8 on the legal-definitions dataset.
It achieves the following results on the evaluation set:


* Loss: 1.3701


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: 64
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #safetensors #bert #fill-mask #generated_from_trainer #dataset-finiteautomata/legal-definitions #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #bert #fill-mask #generated_from_trainer #dataset-finiteautomata/legal-definitions #base_model-google/bert_uncased_L-4_H-512_A-8 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 64
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.21.1
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1