---
license: llama3.1
base_model: Crystalcareai/Meta-llama-3.1-8b-instruct
tags:
- generated_from_trainer
model-index:
- name: data/sft-full
  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: Crystalcareai/Meta-llama-3.1-8b-instruct
bf16: 'True'
chat_template: chatml
dataset_prepared_path: ./sft_processed
dataset_processes: 12
datasets:
- field_messages: messages
  path: sft_dataset
  type: sharegpt
deepspeed: /axolotl/deepspeed_configs/zero3_bf16.json
eval_batch_size: 1
flash_attention: true
gradient_accumulation_steps: 8
gradient_checkpointing: true
learning_rate: 5.0e-06
logging_steps: 1
lr_scheduler: cosine
micro_batch_size: 2
num_epochs: 3
optimizer: adamw_bnb_8bit
output_dir: data/sft-full
pad_to_sequence_len: true
sample_packing: true
save_safetensors: true
save_total_limit: 0
saves_per_epoch: 0
seed: 42
sequence_len: 4096
special_tokens:
  pad_token: <|end_of_text|>
tf32: false
tokens: []
use_tensorboard: true
val_set_size: 0

```

</details><br>

# data/sft-full

This model is a fine-tuned version of [Crystalcareai/Meta-llama-3.1-8b-instruct](https://huggingface.co/Crystalcareai/Meta-llama-3.1-8b-instruct) on the None dataset.

## 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.43.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1