---
library_name: peft
license: llama3.1
base_model: unsloth/Meta-Llama-3.1-8B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: miner_id_3_65eaec89-ddb3-4b65-866f-c621f95eea55_1730931497
  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/Meta-Llama-3.1-8B-Instruct
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - databricks-dolly-15k_train_data.json
  ds_type: json
  path: /workspace/input_data/databricks-dolly-15k_train_data.json
  type:
    field_input: instruction
    field_instruction: context
    field_output: response
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 10
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hours_to_complete: 6
hub_model_id: besimray/miner_id_3_65eaec89-ddb3-4b65-866f-c621f95eea55_1730931497
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: true
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: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 500
micro_batch_size: 5
mlflow_experiment_name: /tmp/databricks-dolly-15k_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: null
sample_packing: false
save_steps: 10
save_strategy: steps
sequence_len: 4096
started_at: '2024-11-06T22:18:17.692838'
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: besimray24-rayon
wandb_mode: online
wandb_project: Public_TuningSN
wandb_run: miner_id_24
wandb_runid: 65eaec89-ddb3-4b65-866f-c621f95eea55
warmup_steps: 10
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# miner_id_3_65eaec89-ddb3-4b65-866f-c621f95eea55_1730931497

This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5331

## 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: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8982        | 0.0014 | 1    | 2.0118          |
| 1.4115        | 0.0141 | 10   | 1.7198          |
| 1.5607        | 0.0282 | 20   | 1.5798          |
| 1.5161        | 0.0424 | 30   | 1.5666          |
| 1.5162        | 0.0565 | 40   | 1.5537          |
| 1.9686        | 0.0706 | 50   | 1.5470          |
| 1.707         | 0.0847 | 60   | 1.5475          |
| 1.6366        | 0.0988 | 70   | 1.5452          |
| 1.1905        | 0.1130 | 80   | 1.5459          |
| 1.3792        | 0.1271 | 90   | 1.5382          |
| 1.459         | 0.1412 | 100  | 1.5392          |
| 1.3699        | 0.1553 | 110  | 1.5354          |
| 1.4439        | 0.1694 | 120  | 1.5356          |
| 1.6577        | 0.1836 | 130  | 1.5331          |
| 1.8126        | 0.1977 | 140  | 1.5347          |
| 1.545         | 0.2118 | 150  | 1.5332          |
| 1.0026        | 0.2259 | 160  | 1.5331          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1