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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wnut_17
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-tiny-finetuned-wnut17-ner
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: wnut_17
type: wnut_17
config: wnut_17
split: train
args: wnut_17
metrics:
- name: Precision
type: precision
value: 0.0
- name: Recall
type: recall
value: 0.0
- name: F1
type: f1
value: 0.0
- name: Accuracy
type: accuracy
value: 0.8960890010322284
---
<!-- 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-tiny-finetuned-wnut17-ner
This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the wnut_17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6054
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8961
## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log | 1.0 | 27 | 1.1060 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 2.0 | 54 | 0.9075 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 3.0 | 81 | 0.7978 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 4.0 | 108 | 0.7333 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 5.0 | 135 | 0.6929 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 6.0 | 162 | 0.6661 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 7.0 | 189 | 0.6477 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 8.0 | 216 | 0.6346 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 9.0 | 243 | 0.6251 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 10.0 | 270 | 0.6182 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 11.0 | 297 | 0.6132 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 12.0 | 324 | 0.6097 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 13.0 | 351 | 0.6073 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 14.0 | 378 | 0.6059 | 0.0 | 0.0 | 0.0 | 0.8961 |
| No log | 15.0 | 405 | 0.6054 | 0.0 | 0.0 | 0.0 | 0.8961 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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