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---
license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: phi_2_scotus
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_scotus
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: 2.0717
- Accuracy: 0.3557
- F1 Macro: 0.1359
- F1 Micro: 0.3557
## 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: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.5187 | 0.32 | 50 | 2.4656 | 0.2171 | 0.0941 | 0.2171 |
| 2.2348 | 0.64 | 100 | 2.3156 | 0.2579 | 0.0980 | 0.2579 |
| 2.2023 | 0.96 | 150 | 2.2223 | 0.2914 | 0.1103 | 0.2914 |
| 2.1145 | 1.27 | 200 | 2.1800 | 0.3064 | 0.1139 | 0.3064 |
| 1.993 | 1.59 | 250 | 2.1359 | 0.3179 | 0.1254 | 0.3179 |
| 1.9609 | 1.91 | 300 | 2.1034 | 0.3457 | 0.1345 | 0.3457 |
| 2.0137 | 2.23 | 350 | 2.1008 | 0.3564 | 0.1382 | 0.3564 |
| 1.9418 | 2.55 | 400 | 2.0717 | 0.3557 | 0.1359 | 0.3557 |
| 1.8887 | 2.87 | 450 | 2.0744 | 0.3636 | 0.1442 | 0.3636 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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