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---
license: mit
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: microsoft/Phi-3-mini-4k-instruct
model-index:
- name: phi3mini_4k_i_RE_QA_alpha8_r_8
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. -->
# phi3mini_4k_i_RE_QA_alpha8_r_8
This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4399
## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7043 | 0.1187 | 100 | 0.5258 |
| 0.5348 | 0.2374 | 200 | 0.4702 |
| 0.5086 | 0.3561 | 300 | 0.4555 |
| 0.4973 | 0.4748 | 400 | 0.4484 |
| 0.4909 | 0.5935 | 500 | 0.4446 |
| 0.4842 | 0.7122 | 600 | 0.4419 |
| 0.4802 | 0.8309 | 700 | 0.4406 |
| 0.4797 | 0.9496 | 800 | 0.4399 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.2.1
- Datasets 2.19.2
- Tokenizers 0.19.1 |