metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: MLMA_GPT_Lab8_custom_trained
results: []
MLMA_GPT_Lab8_custom_trained
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1453
- Precision: 0.5548
- Recall: 0.6041
- F1: 0.5784
- Accuracy: 0.9556
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 474 | 0.1675 | 0.4207 | 0.3972 | 0.4086 | 0.9442 |
| 0.227 | 2.0 | 948 | 0.1660 | 0.4922 | 0.5990 | 0.5404 | 0.9474 |
| 0.1304 | 3.0 | 1422 | 0.1453 | 0.5548 | 0.6041 | 0.5784 | 0.9556 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2