metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: MLMA_GPT_Lab_8
results: []
MLMA_GPT_Lab_8
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1568
- Precision: 0.4432
- Recall: 0.5553
- F1: 0.4929
- Accuracy: 0.9566
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2733 | 1.0 | 679 | 0.1647 | 0.3679 | 0.4142 | 0.3897 | 0.9483 |
| 0.1655 | 2.0 | 1358 | 0.1573 | 0.3803 | 0.5388 | 0.4458 | 0.9517 |
| 0.093 | 3.0 | 2037 | 0.1568 | 0.4432 | 0.5553 | 0.4929 | 0.9566 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2