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license: mit
base_model: microsoft/phi-2
tags:
- generated_from_trainer
model-index:
- name: V0422MADP4D
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. -->
# V0422MADP4D
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: 0.0593
## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2159 | 0.09 | 10 | 1.0244 |
| 0.7518 | 0.18 | 20 | 0.1285 |
| 0.136 | 0.27 | 30 | 0.1050 |
| 0.1153 | 0.36 | 40 | 0.0877 |
| 0.0941 | 0.45 | 50 | 0.0799 |
| 0.0972 | 0.54 | 60 | 0.0782 |
| 0.0877 | 0.63 | 70 | 0.0762 |
| 0.0787 | 0.73 | 80 | 0.0726 |
| 0.0828 | 0.82 | 90 | 0.0708 |
| 0.0793 | 0.91 | 100 | 0.0668 |
| 0.0862 | 1.0 | 110 | 0.0730 |
| 0.0739 | 1.09 | 120 | 0.0651 |
| 0.074 | 1.18 | 130 | 0.0761 |
| 0.0769 | 1.27 | 140 | 0.0646 |
| 0.1095 | 1.36 | 150 | 0.0904 |
| 0.1041 | 1.45 | 160 | 0.0825 |
| 0.082 | 1.54 | 170 | 0.0824 |
| 0.0986 | 1.63 | 180 | 0.0800 |
| 0.0818 | 1.72 | 190 | 0.0727 |
| 0.0828 | 1.81 | 200 | 0.0708 |
| 0.074 | 1.9 | 210 | 0.0673 |
| 0.0697 | 1.99 | 220 | 0.0644 |
| 0.0595 | 2.08 | 230 | 0.0627 |
| 0.0587 | 2.18 | 240 | 0.0648 |
| 0.0585 | 2.27 | 250 | 0.0632 |
| 0.0596 | 2.36 | 260 | 0.0620 |
| 0.0577 | 2.45 | 270 | 0.0610 |
| 0.0545 | 2.54 | 280 | 0.0622 |
| 0.0529 | 2.63 | 290 | 0.0610 |
| 0.0539 | 2.72 | 300 | 0.0601 |
| 0.0589 | 2.81 | 310 | 0.0596 |
| 0.0558 | 2.9 | 320 | 0.0594 |
| 0.0595 | 2.99 | 330 | 0.0593 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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