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# bert-large-cased-finetuned-lowR100-3-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: 2.5250

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 1    | 6.8611          |
| 6.5268        | 2.0   | 2    | 8.5069          |
| 6.5268        | 3.0   | 3    | 6.4383          |
| 6.3552        | 4.0   | 4    | 5.2540          |
| 6.3552        | 5.0   | 5    | 6.2490          |
| 5.5713        | 6.0   | 6    | 5.8587          |
| 5.5713        | 7.0   | 7    | 5.6369          |
| 5.0248        | 8.0   | 8    | 5.1667          |
| 5.0248        | 9.0   | 9    | 4.8407          |
| 4.364         | 10.0  | 10   | 5.0590          |
| 4.364         | 11.0  | 11   | 4.8647          |
| 3.6607        | 12.0  | 12   | 3.3072          |
| 3.6607        | 13.0  | 13   | 3.4963          |
| 3.3901        | 14.0  | 14   | 4.0039          |
| 3.3901        | 15.0  | 15   | 3.5993          |
| 3.1245        | 16.0  | 16   | 2.2179          |
| 3.1245        | 17.0  | 17   | 1.6414          |
| 3.1906        | 18.0  | 18   | 3.1965          |
| 3.1906        | 19.0  | 19   | 3.1463          |
| 2.7243        | 20.0  | 20   | 3.1866          |
| 2.7243        | 21.0  | 21   | 1.0648          |
| 2.944         | 22.0  | 22   | 3.2413          |
| 2.944         | 23.0  | 23   | 3.1838          |
| 2.7114        | 24.0  | 24   | 3.8036          |
| 2.7114        | 25.0  | 25   | 2.2897          |
| 2.4176        | 26.0  | 26   | 3.6953          |
| 2.4176        | 27.0  | 27   | 3.3176          |
| 2.4277        | 28.0  | 28   | 2.9940          |
| 2.4277        | 29.0  | 29   | 3.0186          |
| 2.4099        | 30.0  | 30   | 3.0385          |
| 2.4099        | 31.0  | 31   | 1.9323          |
| 2.2141        | 32.0  | 32   | 2.2952          |
| 2.2141        | 33.0  | 33   | 3.5302          |
| 2.4007        | 34.0  | 34   | 3.7787          |
| 2.4007        | 35.0  | 35   | 3.3718          |
| 2.2619        | 36.0  | 36   | 2.2895          |
| 2.2619        | 37.0  | 37   | 2.7433          |
| 2.4834        | 38.0  | 38   | 3.5129          |
| 2.4834        | 39.0  | 39   | 1.7792          |
| 2.122         | 40.0  | 40   | 2.5250          |


### 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-lowR100-3-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-lowR100-3-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: 2.5250


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