metadata
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
model-index:
- name: fine_tune_bert_output
results: []
fine_tune_bert_output
This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0094
- Overall Precision: 0.9722
- Overall Recall: 0.9722
- Overall F1: 0.9722
- Overall Accuracy: 0.9963
- Number Of Employees F1: 0.9722
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
Training results
| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Number Of Employees F1 |
|---|---|---|---|---|---|---|---|---|
| 0.0011 | 50.0 | 1000 | 0.0046 | 0.9722 | 0.9722 | 0.9722 | 0.9963 | 0.9722 |
| 0.0003 | 100.0 | 2000 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 150.0 | 3000 | 0.0094 | 0.9722 | 0.9722 | 0.9722 | 0.9963 | 0.9722 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3