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# bert-base-uncased-dbpedia_14

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the dbpedia_14 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0547
- Accuracy: 0.9903

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 34650
- training_steps: 346500

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.7757        | 0.03  | 2000  | 0.2732          | 0.9880   |
| 0.1002        | 0.06  | 4000  | 0.0620          | 0.9891   |
| 0.0547        | 0.09  | 6000  | 0.0723          | 0.9879   |
| 0.0558        | 0.12  | 8000  | 0.0678          | 0.9875   |
| 0.0534        | 0.14  | 10000 | 0.0554          | 0.9896   |
| 0.0632        | 0.17  | 12000 | 0.0670          | 0.9888   |
| 0.0612        | 0.2   | 14000 | 0.0733          | 0.9873   |
| 0.0667        | 0.23  | 16000 | 0.0623          | 0.9896   |
| 0.0636        | 0.26  | 18000 | 0.0836          | 0.9868   |
| 0.0705        | 0.29  | 20000 | 0.0776          | 0.9855   |
| 0.0726        | 0.32  | 22000 | 0.0805          | 0.9861   |
| 0.0778        | 0.35  | 24000 | 0.0713          | 0.9870   |
| 0.0713        | 0.38  | 26000 | 0.1277          | 0.9805   |
| 0.0965        | 0.4   | 28000 | 0.0810          | 0.9855   |
| 0.0881        | 0.43  | 30000 | 0.0910          | 0.985    |


### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1
- Datasets 1.6.1
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer", "sibyl"], "datasets": ["dbpedia_14"], "metrics": ["accuracy"], "model-index": [{"name": "bert-base-uncased-dbpedia_14", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "dbpedia_14", "type": "dbpedia_14", "args": "dbpedia_14"}, "metrics": [{"type": "accuracy", "value": 0.9902857142857143, "name": "Accuracy"}]}]}]}
transformers pytorch bert text-classification generated_from_trainer sibyl dataset:dbpedia_14 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #sibyl #dataset-dbpedia_14 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

bert-base-uncased-dbpedia\_14
=============================


This model is a fine-tuned version of bert-base-uncased on the dbpedia\_14 dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0547
* Accuracy: 0.9903


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: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 34650
* training\_steps: 346500


### Training results



### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 34650
* training\_steps: 346500 ### Training results ### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #sibyl #dataset-dbpedia_14 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 34650
* training\_steps: 346500 ### Training results ### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #sibyl #dataset-dbpedia_14 #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 8
* eval\_batch\_size: 16
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 34650
* training\_steps: 346500### Training results### Framework versions


* Transformers 4.10.2
* Pytorch 1.7.1
* Datasets 1.6.1
* Tokenizers 0.10.3