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---
license: apache-2.0
tags:
- generated_from_trainer
- sibyl
datasets:
- dbpedia_14
metrics:
- accuracy
model-index:
- name: bert-base-uncased-dbpedia_14
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: dbpedia_14
type: dbpedia_14
args: dbpedia_14
metrics:
- name: Accuracy
type: accuracy
value: 0.9902857142857143
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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
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