metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: ernie-2.0-base-en-Tweet_About_Disaster_Or_Not
results: []
ernie-2.0-base-en-Tweet_About_Disaster_Or_Not
This model is a fine-tuned version of nghuyong/ernie-2.0-base-en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3622
- Accuracy: 0.9120
- F1: 0.7788
- Recall: 0.8341
- Precision: 0.7303
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.347 | 1.0 | 143 | 0.2663 | 0.8777 | 0.7342 | 0.9100 | 0.6154 |
| 0.2192 | 2.0 | 286 | 0.2292 | 0.9156 | 0.7876 | 0.8436 | 0.7386 |
| 0.132 | 3.0 | 429 | 0.2629 | 0.9129 | 0.7843 | 0.8531 | 0.7258 |
| 0.0767 | 4.0 | 572 | 0.3266 | 0.9120 | 0.7807 | 0.8436 | 0.7265 |
| 0.0532 | 5.0 | 715 | 0.3622 | 0.9120 | 0.7788 | 0.8341 | 0.7303 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.12.1