metadata
base_model: bert-base-chinese
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: Misinformation-Covid-bert-base-chinese
results: []
Misinformation-Covid-bert-base-chinese
This model is a fine-tuned version of bert-base-chinese on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6859
- F1: 0.3191
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6995 | 1.0 | 201 | 0.6661 | 0.0417 |
| 0.6843 | 2.0 | 402 | 0.6824 | 0.2745 |
| 0.665 | 3.0 | 603 | 0.6240 | 0.3306 |
| 0.6208 | 4.0 | 804 | 0.6211 | 0.3141 |
| 0.5939 | 5.0 | 1005 | 0.6095 | 0.3231 |
| 0.6094 | 6.0 | 1206 | 0.6216 | 0.3276 |
| 0.5177 | 7.0 | 1407 | 0.6437 | 0.3333 |
| 0.5092 | 8.0 | 1608 | 0.6585 | 0.3519 |
| 0.4781 | 9.0 | 1809 | 0.6867 | 0.3333 |
| 0.4706 | 10.0 | 2010 | 0.6859 | 0.3191 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3