---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3
tags:
- axolotl
- generated_from_trainer
model-index:
- name: empower-functions-llama3-1-8b-with-more-neg-5
  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
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer

chat_template: llama3

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
- path: ./hf_data/function_not_used_no_unicode_7500.jsonl
  type: sharegpt
  conversation: llama-3
- path: ./hf_data/function_used_training_shuffled_no_unicode_without_examples_corrected_updated.jsonl
  type: sharegpt
  conversation: llama-3
- path: ./hf_data/parallel_data_training_no_unicode_updated.jsonl
  type: sharegpt
  conversation: llama-3
- path: ./hf_data/parallel_data_training_single_function.jsonl  
  type: sharegpt
  conversation: llama-3   
- path: ./hf_data/function_not_used_new.jsonl
  type: sharegpt
  conversation: llama-3   
- path: ./hf_data/lambda_dataset_100.jsonl
  type: sharegpt
  conversation: llama-3  
- path: ./hf_data/function_not_used_new_more.jsonl
  type: sharegpt
  conversation: llama-3

dataset_prepared_path: last_run_prepared
val_set_size: 0.025

output_dir: ../empower-functions-llama3-1-8b-with-more-neg-5

hub_model_id: empower-dev-staging/empower-functions-llama3-1-8b-with-more-neg-5
sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

adapter: lora
lora_model_dir:
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
s2_attention:

warmup_steps: 10

eval_batch_size: 2
eval_max_new_tokens: 256
eval_steps: 0.1
eval_table_size: null

saves_per_epoch: 4

debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
   pad_token: <|end_of_text|>


```

</details><br>

# empower-functions-llama3-1-8b-with-more-neg-5

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0968

## 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
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9991        | 0.0033 | 1    | 0.9484          |
| 0.1914        | 0.1016 | 31   | 0.1566          |
| 0.1563        | 0.2033 | 62   | 0.1268          |
| 0.0598        | 0.3049 | 93   | 0.1189          |
| 0.0936        | 0.4066 | 124  | 0.1115          |
| 0.0926        | 0.5082 | 155  | 0.1067          |
| 0.0829        | 0.6098 | 186  | 0.1024          |
| 0.1267        | 0.7115 | 217  | 0.0996          |
| 0.0827        | 0.8131 | 248  | 0.0978          |
| 0.0991        | 0.9148 | 279  | 0.0968          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1