|
|
--- |
|
|
license: mit |
|
|
base_model: microsoft/phi-2 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: phi_2_amazon |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# phi_2_amazon |
|
|
|
|
|
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.6451 |
|
|
- Accuracy: 0.5659 |
|
|
- F1 Macro: 0.4655 |
|
|
- F1 Micro: 0.5659 |
|
|
|
|
|
## 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-06 |
|
|
- train_batch_size: 16 |
|
|
- eval_batch_size: 16 |
|
|
- seed: 42 |
|
|
- distributed_type: multi-GPU |
|
|
- num_devices: 2 |
|
|
- total_train_batch_size: 32 |
|
|
- total_eval_batch_size: 32 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 1.0 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:| |
|
|
| 3.2062 | 0.13 | 50 | 3.1866 | 0.0922 | 0.0634 | 0.0922 | |
|
|
| 2.9492 | 0.26 | 100 | 2.9088 | 0.1528 | 0.1081 | 0.1528 | |
|
|
| 2.6945 | 0.39 | 150 | 2.6944 | 0.2286 | 0.1693 | 0.2286 | |
|
|
| 2.457 | 0.53 | 200 | 2.4137 | 0.3373 | 0.2529 | 0.3373 | |
|
|
| 2.0566 | 0.66 | 250 | 2.0552 | 0.4499 | 0.3541 | 0.4499 | |
|
|
| 1.7723 | 0.79 | 300 | 1.7765 | 0.5264 | 0.4225 | 0.5264 | |
|
|
| 1.7695 | 0.92 | 350 | 1.6451 | 0.5659 | 0.4655 | 0.5659 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.39.0.dev0 |
|
|
- Pytorch 2.2.1+cu121 |
|
|
- Datasets 2.18.0 |
|
|
- Tokenizers 0.15.2 |
|
|
|
