---
license: mit
base_model: microsoft/Phi-3-mini-4k-instruct
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- trl-lib/kto-mix-14k
- chaoweihuang/lf-response-phi3-f1_100_0.7-fg0.5
model-index:
- name: kto-mix-14k-lf-response-phi3-f1_100_0.7-fg0.5-kto-fg-fgudw4.0
  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. -->

# kto-mix-14k-lf-response-phi3-f1_100_0.7-fg0.5-kto-fg-fgudw4.0

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 trl-lib/kto-mix-14k and the chaoweihuang/lf-response-phi3-f1_100_0.7-fg0.5 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4815
- Rewards/chosen: -0.6601
- Logps/chosen: -299.7121
- Rewards/rejected: -2.6435
- Logps/rejected: -364.3744
- Rewards/margins: 1.9834
- Kl: 0.0081
- Fg Kl: nan
- Fg Rewards/chosen Sum: 0.0694
- Fg Logps/policy Chosen: -15.2781
- Fg Logps/reference Chosen: -14.9295
- Count/fg Chosen: 16.0137
- Fg Rewards/rejected Sum: -0.3623
- Fg Logps/policy Rejected: -19.6552
- Fg Logps/reference Rejected: -18.7868
- Count/fg Rejected: 4.0824
- Fg Logps/policy Kl: -21.1260
- Fg Logps/reference Kl: -20.2070
- Fg Loss: 0.7365

## 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-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Logps/chosen | Rewards/rejected | Logps/rejected | Rewards/margins | Kl     | Fg Kl | Fg Rewards/chosen Sum | Fg Logps/policy Chosen | Fg Logps/reference Chosen | Count/fg Chosen | Fg Rewards/rejected Sum | Fg Logps/policy Rejected | Fg Logps/reference Rejected | Count/fg Rejected | Fg Logps/policy Kl | Fg Logps/reference Kl | Fg Loss |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:--------------:|:---------------:|:------:|:-----:|:---------------------:|:----------------------:|:-------------------------:|:---------------:|:-----------------------:|:------------------------:|:---------------------------:|:-----------------:|:------------------:|:---------------------:|:-------:|
| 0.4495        | 0.4103 | 400  | 0.4978          | -1.0397        | -303.5076    | -2.7182          | -365.1212      | 1.6785          | 0.0054 | nan   | -1.3184               | -16.1070               | -14.9295                  | 16.0137         | -0.5732                 | -20.2671                 | -18.7868                    | 4.0824            | -21.1826           | -20.2070              | 0.7449  |
| 0.5189        | 0.8206 | 800  | 0.4815          | -0.6601        | -299.7121    | -2.6435          | -364.3744      | 1.9834          | 0.0081 | nan   | 0.0694                | -15.2781               | -14.9295                  | 16.0137         | -0.3623                 | -19.6552                 | -18.7868                    | 4.0824            | -21.1260           | -20.2070              | 0.7365  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1