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# bert-large-cased-finetuned-lowR100-0-cased-DA-40

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: 1.9481

## 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    | 1.8079          |
| 2.0032        | 2.0   | 2    | 3.1228          |
| 2.0032        | 3.0   | 3    | 1.9553          |
| 1.9122        | 4.0   | 4    | 2.1789          |
| 1.9122        | 5.0   | 5    | 1.8698          |
| 1.9936        | 6.0   | 6    | 2.1649          |
| 1.9936        | 7.0   | 7    | 3.3564          |
| 1.8624        | 8.0   | 8    | 2.6206          |
| 1.8624        | 9.0   | 9    | 2.0358          |
| 1.8051        | 10.0  | 10   | 1.9754          |
| 1.8051        | 11.0  | 11   | 2.5270          |
| 2.0363        | 12.0  | 12   | 1.8028          |
| 2.0363        | 13.0  | 13   | 2.0974          |
| 1.7005        | 14.0  | 14   | 1.2336          |
| 1.7005        | 15.0  | 15   | 2.0583          |
| 1.6696        | 16.0  | 16   | 3.1515          |
| 1.6696        | 17.0  | 17   | 2.3699          |
| 1.5171        | 18.0  | 18   | 2.5653          |
| 1.5171        | 19.0  | 19   | 1.6895          |
| 1.573         | 20.0  | 20   | 1.7983          |
| 1.573         | 21.0  | 21   | 3.0257          |
| 1.5831        | 22.0  | 22   | 2.8107          |
| 1.5831        | 23.0  | 23   | 1.6412          |
| 1.6265        | 24.0  | 24   | 1.9859          |
| 1.6265        | 25.0  | 25   | 1.7744          |
| 1.6744        | 26.0  | 26   | 2.7989          |
| 1.6744        | 27.0  | 27   | 1.7943          |
| 1.5041        | 28.0  | 28   | 1.5538          |
| 1.5041        | 29.0  | 29   | 3.9907          |
| 1.5154        | 30.0  | 30   | 0.8862          |
| 1.5154        | 31.0  | 31   | 1.7290          |
| 1.5841        | 32.0  | 32   | 1.7470          |
| 1.5841        | 33.0  | 33   | 1.9897          |
| 1.6299        | 34.0  | 34   | 1.7316          |
| 1.6299        | 35.0  | 35   | 1.7352          |
| 1.6617        | 36.0  | 36   | 1.7413          |
| 1.6617        | 37.0  | 37   | 2.7554          |
| 1.3198        | 38.0  | 38   | 2.7426          |
| 1.3198        | 39.0  | 39   | 1.7127          |
| 1.6463        | 40.0  | 40   | 1.6030          |


### 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-lowR100-0-cased-DA-40", "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-lowR100-0-cased-DA-40
================================================


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: 1.9481


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