---
library_name: peft
license: llama3
base_model: unsloth/llama-3-8b-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 6813e4a9-59b5-485f-b2d9-38de43e7887d
  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: lora
base_model: unsloth/llama-3-8b-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 4068f8101ab29bee_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/4068f8101ab29bee_train_data.json
  type:
    field_instruction: infobox
    field_output: summary
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 4
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: dimasik87/6813e4a9-59b5-485f-b2d9-38de43e7887d
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_memory:
  0: 70GiB
max_steps: 50
micro_batch_size: 1
mlflow_experiment_name: /tmp/4068f8101ab29bee_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 4
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 4
sequence_len: 2028
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 6813e4a9-59b5-485f-b2d9-38de43e7887d
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 6813e4a9-59b5-485f-b2d9-38de43e7887d
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 6813e4a9-59b5-485f-b2d9-38de43e7887d

This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct](https://huggingface.co/unsloth/llama-3-8b-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2675

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 50

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7376        | 0.0027 | 1    | 0.7193          |
| 0.6835        | 0.0108 | 4    | 0.6272          |
| 0.3742        | 0.0215 | 8    | 0.3806          |
| 0.2788        | 0.0323 | 12   | 0.3253          |
| 0.5915        | 0.0431 | 16   | 0.2901          |
| 0.2583        | 0.0538 | 20   | 0.2826          |
| 0.2147        | 0.0646 | 24   | 0.2890          |
| 0.2077        | 0.0754 | 28   | 0.2844          |
| 0.4248        | 0.0861 | 32   | 0.2731          |
| 0.3099        | 0.0969 | 36   | 0.2734          |
| 0.2465        | 0.1077 | 40   | 0.2704          |
| 0.2693        | 0.1184 | 44   | 0.2685          |
| 0.231         | 0.1292 | 48   | 0.2675          |


### Framework versions

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