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# distilroberta-base-testingSB

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on a company specific, Danish dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0403

## Model description

Customer-specific model used to embed asset management work orders in Danish

## Intended uses & limitations

Customer-specific and trained for unsupervised categorization tasks

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results
Epoch	Training Loss	Validation Loss
1	0.988500	1.056376
2	0.996300	1.027803
3	0.990300	1.040270

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.98850        | 1.0   | 1461 | 1.5211          |
| 1.3179        | 2.0   | 2922 | 1.3314          |
| 1.1931        | 3.0   | 4383 | 1.2530          |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "distilroberta-base-testingSB", "results": []}]}
transformers pytorch tensorboard roberta fill-mask generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #roberta #fill-mask #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilroberta-base-testingSB
============================


This model is a fine-tuned version of distilroberta-base on a company specific, Danish dataset.
It achieves the following results on the evaluation set:


* Loss: 1.0403


Model description
-----------------


Customer-specific model used to embed asset management work orders in Danish


Intended uses & limitations
---------------------------


Customer-specific and trained for unsupervised categorization tasks


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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0


### Training results


Epoch Training Loss Validation Loss
1 0.988500 1.056376
2 0.996300 1.027803
3 0.990300 1.040270



### Framework versions


* Transformers 4.12.5
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results


Epoch Training Loss Validation Loss
1 0.988500 1.056376
2 0.996300 1.027803
3 0.990300 1.040270 ### Framework versions


* Transformers 4.12.5
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #roberta #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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0 ### Training results


Epoch Training Loss Validation Loss
1 0.988500 1.056376
2 0.996300 1.027803
3 0.990300 1.040270 ### Framework versions


* Transformers 4.12.5
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #roberta #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: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3.0### Training results


Epoch Training Loss Validation Loss
1 0.988500 1.056376
2 0.996300 1.027803
3 0.990300 1.040270### Framework versions


* Transformers 4.12.5
* Pytorch 1.10.0+cu111
* Datasets 1.15.1
* Tokenizers 0.10.3