---
license: mit
base_model: microsoft/Phi-3-mini-128k-instruct
tags:
- generated_from_trainer
model-index:
- name: CodePhi-3-mini-128k-instruct-APPS1.4k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CodePhi-3-mini-128k-instruct-APPS1.4k

This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6034

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 1400

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5991        | 0.1429 | 200  | 0.6309          |
| 0.579         | 0.2857 | 400  | 0.6142          |
| 0.5665        | 0.4286 | 600  | 0.6070          |
| 0.545         | 0.5714 | 800  | 0.6044          |
| 0.5199        | 0.7143 | 1000 | 0.6035          |
| 0.5763        | 0.8571 | 1200 | 0.6035          |
| 0.5594        | 1.0    | 1400 | 0.6034          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1