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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-ner-TRANS
results: []
---
<!-- 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. -->
# distilbert-base-uncased-finetuned-ner-TRANS
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1053
- Precision: 0.7911
- Recall: 0.8114
- F1: 0.8011
- Accuracy: 0.9815
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.077 | 1.0 | 3762 | 0.0724 | 0.7096 | 0.7472 | 0.7279 | 0.9741 |
| 0.0538 | 2.0 | 7524 | 0.0652 | 0.7308 | 0.7687 | 0.7493 | 0.9766 |
| 0.0412 | 3.0 | 11286 | 0.0643 | 0.7672 | 0.7875 | 0.7772 | 0.9788 |
| 0.0315 | 4.0 | 15048 | 0.0735 | 0.7646 | 0.7966 | 0.7803 | 0.9793 |
| 0.0249 | 5.0 | 18810 | 0.0772 | 0.7805 | 0.7981 | 0.7892 | 0.9801 |
| 0.0213 | 6.0 | 22572 | 0.0783 | 0.7829 | 0.8063 | 0.7944 | 0.9805 |
| 0.0187 | 7.0 | 26334 | 0.0858 | 0.7821 | 0.8010 | 0.7914 | 0.9809 |
| 0.0157 | 8.0 | 30096 | 0.0860 | 0.7837 | 0.8120 | 0.7976 | 0.9812 |
| 0.0122 | 9.0 | 33858 | 0.0963 | 0.7857 | 0.8129 | 0.7990 | 0.9813 |
| 0.0107 | 10.0 | 37620 | 0.0993 | 0.7934 | 0.8089 | 0.8010 | 0.9812 |
| 0.0091 | 11.0 | 41382 | 0.1031 | 0.7882 | 0.8123 | 0.8001 | 0.9814 |
| 0.0083 | 12.0 | 45144 | 0.1053 | 0.7911 | 0.8114 | 0.8011 | 0.9815 |
### Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1
- Datasets 2.0.0
- Tokenizers 0.10.3
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