peft safetensors llama axolotl generated_from_trainer base_model:llamafactory/tiny-random-Llama-3 base_model:adapter:llamafactory/tiny-random-Llama-3 license:apache-2.0 region:us
---
base_model: llamafactory/tiny-random-Llama-3
library_name: peft
license: apache-2.0
tags:
- axolotl
- generated_from_trainer
model-index:
- name: e78c5238-c9e3-45b1-92f4-7579efbf91ab
  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: llamafactory/tiny-random-Llama-3
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 420d808b1b64ffc0_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/420d808b1b64ffc0_train_data.json
  type:
    field_instruction: source
    field_output: good-translation
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
device_map:
  ? ''
  : 0,1,2,3,4,5,6,7
early_stopping_patience: 2
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: Alphatao/e78c5238-c9e3-45b1-92f4-7579efbf91ab
hub_repo: null
hub_strategy: null
hub_token: null
learning_rate: 0.0002
load_best_model_at_end: true
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
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
- down_proj
- up_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 5376
micro_batch_size: 4
mlflow_experiment_name: /tmp/420d808b1b64ffc0_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 2
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 2048
special_tokens:
  pad_token: <|eot_id|>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.04
wandb_entity: null
wandb_mode: online
wandb_name: 70c61e5c-5f68-4639-804d-89212f8c7742
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 70c61e5c-5f68-4639-804d-89212f8c7742
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# e78c5238-c9e3-45b1-92f4-7579efbf91ab

This model is a fine-tuned version of [llamafactory/tiny-random-Llama-3](https://huggingface.co/llamafactory/tiny-random-Llama-3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 11.7309

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 2123

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 11.7614       | 0.0009 | 1    | 11.7621         |
| 11.739        | 0.0942 | 100  | 11.7406         |
| 11.7415       | 0.1885 | 200  | 11.7367         |
| 11.7343       | 0.2827 | 300  | 11.7364         |
| 11.7477       | 0.3769 | 400  | 11.7362         |
| 11.7403       | 0.4711 | 500  | 11.7359         |
| 11.7353       | 0.5654 | 600  | 11.7353         |
| 11.7411       | 0.6596 | 700  | 11.7345         |
| 11.7356       | 0.7538 | 800  | 11.7339         |
| 11.7365       | 0.8481 | 900  | 11.7330         |
| 11.7353       | 0.9423 | 1000 | 11.7325         |
| 13.0327       | 1.0365 | 1100 | 11.7322         |
| 11.6725       | 1.1307 | 1200 | 11.7318         |
| 11.7828       | 1.2250 | 1300 | 11.7315         |
| 11.8239       | 1.3192 | 1400 | 11.7314         |
| 10.3118       | 1.4134 | 1500 | 11.7312         |
| 12.9101       | 1.5077 | 1600 | 11.7311         |
| 10.6316       | 1.6019 | 1700 | 11.7310         |
| 10.6872       | 1.6961 | 1800 | 11.7309         |
| 11.5374       | 1.7903 | 1900 | 11.7309         |
| 12.3307       | 1.8846 | 2000 | 11.7309         |
| 10.9047       | 1.9788 | 2100 | 11.7309         |


### Framework versions

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