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# distilbert-base-uncased-finetuned-wikiandmark_epoch20

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0561
- Accuracy: 0.9944

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0224        | 1.0   | 1859  | 0.0277          | 0.9919   |
| 0.0103        | 2.0   | 3718  | 0.0298          | 0.9925   |
| 0.0047        | 3.0   | 5577  | 0.0429          | 0.9924   |
| 0.0038        | 4.0   | 7436  | 0.0569          | 0.9922   |
| 0.0019        | 5.0   | 9295  | 0.0554          | 0.9936   |
| 0.0028        | 6.0   | 11154 | 0.0575          | 0.9928   |
| 0.002         | 7.0   | 13013 | 0.0544          | 0.9926   |
| 0.0017        | 8.0   | 14872 | 0.0553          | 0.9935   |
| 0.001         | 9.0   | 16731 | 0.0498          | 0.9924   |
| 0.0001        | 10.0  | 18590 | 0.0398          | 0.9934   |
| 0.0           | 11.0  | 20449 | 0.0617          | 0.9935   |
| 0.0002        | 12.0  | 22308 | 0.0561          | 0.9944   |
| 0.0002        | 13.0  | 24167 | 0.0755          | 0.9934   |
| 0.0           | 14.0  | 26026 | 0.0592          | 0.9941   |
| 0.0           | 15.0  | 27885 | 0.0572          | 0.9939   |
| 0.0           | 16.0  | 29744 | 0.0563          | 0.9941   |
| 0.0           | 17.0  | 31603 | 0.0587          | 0.9936   |
| 0.0005        | 18.0  | 33462 | 0.0673          | 0.9937   |
| 0.0           | 19.0  | 35321 | 0.0651          | 0.9933   |
| 0.0           | 20.0  | 37180 | 0.0683          | 0.9936   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "distilbert-base-uncased-finetuned-wikiandmark_epoch20", "results": []}]}
transformers pytorch tensorboard distilbert text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

distilbert-base-uncased-finetuned-wikiandmark\_epoch20
======================================================


This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0561
* Accuracy: 0.9944


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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #distilbert #text-classification #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: 32
* eval\_batch\_size: 32
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.20.1
* Pytorch 1.12.0+cu113
* Datasets 2.3.2
* Tokenizers 0.12.1