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# bert-large-cased-finetuned-lowR100-2-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: 2.7801

## 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: 40.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.4515        | 1.0   | 1    | 8.1791          |
| 6.4671        | 2.0   | 2    | 6.0155          |
| 6.533         | 3.0   | 3    | 5.9784          |
| 5.8654        | 4.0   | 4    | 5.2092          |
| 5.5458        | 5.0   | 5    | 6.1062          |
| 5.1806        | 6.0   | 6    | 5.0913          |
| 4.8797        | 7.0   | 7    | 4.3025          |
| 4.6975        | 8.0   | 8    | 4.8598          |
| 4.2859        | 9.0   | 9    | 4.2301          |
| 4.3584        | 10.0  | 10   | 4.0683          |
| 4.0203        | 11.0  | 11   | 2.7986          |
| 3.977         | 12.0  | 12   | 4.1575          |
| 3.4077        | 13.0  | 13   | 3.6507          |
| 3.313         | 14.0  | 14   | 2.8674          |
| 3.0962        | 15.0  | 15   | 2.5103          |
| 2.8883        | 16.0  | 16   | 3.1318          |
| 2.9623        | 17.0  | 17   | 2.1316          |
| 2.5544        | 18.0  | 18   | 2.7741          |
| 2.9957        | 19.0  | 19   | 2.9045          |
| 2.749         | 20.0  | 20   | 2.8824          |
| 2.291         | 21.0  | 21   | 2.7450          |
| 2.3373        | 22.0  | 22   | 2.3774          |
| 2.6506        | 23.0  | 23   | 2.5515          |
| 2.6736        | 24.0  | 24   | 2.2106          |
| 2.3845        | 25.0  | 25   | 2.3166          |
| 2.3762        | 26.0  | 26   | 2.3221          |
| 2.4184        | 27.0  | 27   | 2.8996          |
| 2.6826        | 28.0  | 28   | 2.1793          |
| 2.4678        | 29.0  | 29   | 2.4268          |
| 2.2998        | 30.0  | 30   | 1.8153          |
| 2.7085        | 31.0  | 31   | 2.4401          |
| 2.1231        | 32.0  | 32   | 3.3329          |
| 2.1349        | 33.0  | 33   | 1.9675          |
| 2.4647        | 34.0  | 34   | 3.0172          |
| 2.3552        | 35.0  | 35   | 1.8550          |
| 2.2843        | 36.0  | 36   | 2.7737          |
| 2.2164        | 37.0  | 37   | 3.4890          |
| 2.2118        | 38.0  | 38   | 3.4251          |
| 2.3133        | 39.0  | 39   | 2.6806          |
| 1.9773        | 40.0  | 40   | 2.7801          |


### 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-lowR100-2-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-lowR100-2-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: 2.7801


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: 40.0
* 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: 40.0
* 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: 40.0
* 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: 40.0
* 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