---
library_name: peft
license: mit
base_model: unsloth/Phi-3-medium-4k-instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 65665304-fb0e-4e82-8266-aba26a9f6ca0
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
adapter: qlora
base_model: unsloth/Phi-3-medium-4k-instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 9cd9d6ddd992cd94_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/9cd9d6ddd992cd94_train_data.json
  type:
    field_input: input
    field_instruction: system_prompt
    field_output: reference_answer
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 5
eval_max_new_tokens: 128
eval_steps: 200
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: error577/65665304-fb0e-4e82-8266-aba26a9f6ca0
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.15
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 8
lora_target_linear: true
loraplus_lr_ratio: 16
lr_scheduler: constant_with_warmup
micro_batch_size: 2
mlflow_experiment_name: /tmp/9cd9d6ddd992cd94_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: paged_ademamix_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
restore_best_weights: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 200

sequence_len: 256
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.002
wandb_entity: null
wandb_mode: online
wandb_name: 23ddb23c-7a61-40c1-9f72-48b94618385b
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 23ddb23c-7a61-40c1-9f72-48b94618385b
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 65665304-fb0e-4e82-8266-aba26a9f6ca0

This model is a fine-tuned version of [unsloth/Phi-3-medium-4k-instruct](https://huggingface.co/unsloth/Phi-3-medium-4k-instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0604

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.PAGED_ADEMAMIX_8BIT and the args are:
No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 10
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.8043        | 0.0001 | 1    | 1.1370          |
| 3.1671        | 0.0212 | 200  | 0.3959          |
| 1.3667        | 0.0424 | 400  | 0.1787          |
| 1.3113        | 0.0637 | 600  | 0.0892          |
| 0.5292        | 0.0849 | 800  | 0.2110          |
| 0.3196        | 0.1061 | 1000 | 0.0461          |
| 0.5194        | 0.1273 | 1200 | 0.0534          |
| 3.7961        | 0.1485 | 1400 | 0.0516          |
| 0.3986        | 0.1698 | 1600 | 0.0575          |
| 0.3479        | 0.1910 | 1800 | 0.0679          |
| 0.777         | 0.2122 | 2000 | 0.0604          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1