metadata
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: training_dir
results: []
training_dir
This model is a fine-tuned version of albert-base-v2 on an Spam Data Collection dataset. It achieves the following results on the evaluation set:
- Loss: 0.0393
- Accuracy: 0.9946
- F1 Score: 0.9946
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- 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 | Accuracy | F1 Score |
|---|---|---|---|---|---|
| No log | 1.0 | 244 | 0.1070 | 0.9785 | 0.9785 |
| No log | 2.0 | 488 | 0.0673 | 0.9880 | 0.9880 |
| 0.0885 | 3.0 | 732 | 0.0293 | 0.9946 | 0.9946 |
| 0.0885 | 4.0 | 976 | 0.0280 | 0.9964 | 0.9964 |
| 0.0306 | 5.0 | 1220 | 0.0355 | 0.9952 | 0.9952 |
| 0.0306 | 6.0 | 1464 | 0.0364 | 0.9952 | 0.9952 |
| 0.0087 | 7.0 | 1708 | 0.0448 | 0.9946 | 0.9946 |
| 0.0087 | 8.0 | 1952 | 0.0618 | 0.9922 | 0.9922 |
| 0.0047 | 9.0 | 2196 | 0.0420 | 0.9946 | 0.9946 |
| 0.0047 | 10.0 | 2440 | 0.0393 | 0.9946 | 0.9946 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3