metadata
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Phi-3-mini-4k-instruct-mbti
results: []
Phi-3-mini-4k-instruct-mbti
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6615
- Accuracy: 0.6220
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.7155 | 0.1977 | 500 | 0.7196 | 0.5898 |
0.6873 | 0.3955 | 1000 | 0.6776 | 0.5931 |
0.6841 | 0.5932 | 1500 | 0.6620 | 0.6058 |
0.6746 | 0.7909 | 2000 | 0.6615 | 0.6220 |
0.6655 | 0.9886 | 2500 | 0.6647 | 0.6133 |
0.6092 | 1.1864 | 3000 | 0.6873 | 0.5716 |
0.5661 | 1.3841 | 3500 | 0.7262 | 0.6092 |
0.5565 | 1.5818 | 4000 | 0.6938 | 0.6185 |
0.5308 | 1.7795 | 4500 | 0.7100 | 0.6060 |
0.5236 | 1.9773 | 5000 | 0.7046 | 0.6127 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1