metadata
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_model_2
results: []
fine_tuned_model_2
This model is a fine-tuned version of albert/albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1547
- Accuracy: 0.9730
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 28 | 0.5030 | 0.9189 |
| No log | 2.0 | 56 | 0.1776 | 0.9640 |
| No log | 3.0 | 84 | 1.1016 | 0.2793 |
| No log | 4.0 | 112 | 0.7159 | 0.8739 |
| No log | 5.0 | 140 | 0.1969 | 0.9550 |
| No log | 6.0 | 168 | 0.1550 | 0.9640 |
| No log | 7.0 | 196 | 0.1547 | 0.9730 |
| No log | 8.0 | 224 | 0.1794 | 0.9640 |
| No log | 9.0 | 252 | 0.1822 | 0.9640 |
| No log | 10.0 | 280 | 0.1845 | 0.9640 |
| No log | 11.0 | 308 | 0.1834 | 0.9640 |
| No log | 12.0 | 336 | 0.1827 | 0.9640 |
| No log | 13.0 | 364 | 0.1694 | 0.9730 |
| No log | 14.0 | 392 | 0.1714 | 0.9730 |
| No log | 15.0 | 420 | 0.1737 | 0.9730 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2