---
library_name: peft
license: cc-by-sa-4.0
base_model: defog/llama-3-sqlcoder-8b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: ff810066-31fd-4436-a2c4-296c7f507694
  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: defog/llama-3-sqlcoder-8b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 9a795b17b199f7fe_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/9a795b17b199f7fe_train_data.json
  type:
    field_instruction: text
    field_output: label
    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: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 8
gradient_checkpointing: false
group_by_length: false
hub_model_id: leixa/ff810066-31fd-4436-a2c4-296c7f507694
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0001
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
lora_alpha: 128
lora_dropout: 0.1
lora_fan_in_fan_out: true
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/9a795b17b199f7fe_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: false
sample_packing: false
saves_per_epoch: 4
sequence_len: 512
special_tokens:
  pad_token: <|eot_id|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: leixa-personal
wandb_mode: online
wandb_name: ff810066-31fd-4436-a2c4-296c7f507694
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: ff810066-31fd-4436-a2c4-296c7f507694
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# ff810066-31fd-4436-a2c4-296c7f507694

This model is a fine-tuned version of [defog/llama-3-sqlcoder-8b](https://huggingface.co/defog/llama-3-sqlcoder-8b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0775

## 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: 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: 393

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0076 | 1    | 16.8733         |
| 0.2599        | 0.2519 | 33   | 0.1527          |
| 0.0761        | 0.5038 | 66   | 0.1225          |
| 0.1768        | 0.7557 | 99   | 0.1619          |
| 0.0645        | 1.0076 | 132  | 0.1234          |
| 0.0688        | 1.2595 | 165  | 0.1283          |
| 0.0478        | 1.5115 | 198  | 0.1044          |
| 0.0468        | 1.7634 | 231  | 0.0829          |
| 0.0539        | 2.0153 | 264  | 0.0769          |
| 0.0326        | 2.2672 | 297  | 0.0764          |
| 0.0971        | 2.5191 | 330  | 0.0781          |
| 0.0526        | 2.7710 | 363  | 0.0775          |


### Framework versions

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