metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: albert-base-v2-Tweet_About_Disaster_Or_Not
results: []
albert-base-v2-Tweet_About_Disaster_Or_Not
This model is a fine-tuned version of albert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2899
- Accuracy: 0.8989
- F1: 0.7784
- Recall: 0.8523
- Precision: 0.7163
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 |
|---|---|---|---|---|---|---|---|
| 0.3598 | 1.0 | 143 | 0.3025 | 0.8795 | 0.7495 | 0.8650 | 0.6613 |
| 0.234 | 2.0 | 286 | 0.2899 | 0.8989 | 0.7784 | 0.8523 | 0.7163 |
| 0.1557 | 3.0 | 429 | 0.3424 | 0.9156 | 0.7904 | 0.7637 | 0.8190 |
| 0.0871 | 4.0 | 572 | 0.4189 | 0.9182 | 0.7901 | 0.7384 | 0.8495 |
| 0.0517 | 5.0 | 715 | 0.4396 | 0.9200 | 0.8043 | 0.7890 | 0.8202 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.9.0
- Tokenizers 0.12.1