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# bert-large-cased-finetuned-lowR10-0-cased-DA-20

This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8706

## 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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.534         | 1.0   | 1    | 3.3267          |
| 3.4023        | 2.0   | 2    | 1.9169          |
| 3.9478        | 3.0   | 3    | 4.7299          |
| 2.7598        | 4.0   | 4    | 1.9790          |
| 3.5718        | 5.0   | 5    | 2.9120          |
| 2.554         | 6.0   | 6    | 4.7168          |
| 2.3288        | 7.0   | 7    | 3.0791          |
| 4.2772        | 8.0   | 8    | 5.0675          |
| 3.0613        | 9.0   | 9    | 2.8924          |
| 2.6295        | 10.0  | 10   | 4.0580          |
| 1.1492        | 11.0  | 11   | 1.9058          |
| 2.4894        | 12.0  | 12   | 3.3881          |
| 1.0674        | 13.0  | 13   | 4.1820          |
| 1.0408        | 14.0  | 14   | 1.3132          |
| 2.4876        | 15.0  | 15   | 1.8314          |
| 1.8407        | 16.0  | 16   | 2.4077          |
| 2.3834        | 17.0  | 17   | 2.9627          |
| 3.0375        | 18.0  | 18   | 2.5811          |
| 1.8393        | 19.0  | 19   | 2.4138          |
| 1.8369        | 20.0  | 20   | 2.2895          |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bert-large-cased-finetuned-lowR10-0-cased-DA-20", "results": []}]}
transformers pytorch tensorboard bert fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

bert-large-cased-finetuned-lowR10-0-cased-DA-20
===============================================


This model is a fine-tuned version of bert-large-cased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 3.8706


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: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #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: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #bert #fill-mask #generated_from_trainer #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: 30
* eval\_batch\_size: 30
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.26.0
* Pytorch 1.13.1+cu116
* Datasets 2.9.0
* Tokenizers 0.13.2