---
base_model: NousResearch/Hermes-3-Llama-3.1-8B
library_name: peft
license: llama3
tags:
- generated_from_trainer
model-index:
- name: lora-out
  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. -->

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<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
###
# Model Configuration: LLaMA-3 70B
###

base_model: NousResearch/Hermes-3-Llama-3.1-8B
# base_model: NousResearch/Hermes-3-Llama-3.1-70B
sequence_len: 1024

# base model weight quantization
load_in_8bit: true
# load_in_4bit: true

# attention implementation
flash_attention: true

# finetuned adapter config
adapter: lora
lora_model_dir:
lora_r: 16
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_modules_to_save: # required when adding new tokens to LLaMA/Mistral
  - embed_tokens
  - lm_head
# for details, see https://github.com/huggingface/peft/issues/334#issuecomment-1561727994

###
# Dataset Configuration: sqlqa
###
# datasets:
#   - path: data.jsonl
#     type: alpaca

datasets:
  - path: data.jsonl
    ds_type: json
    type:
      field_instruction: instruction
      field_input: input
      field_output: output
      format: |-
        [INST] {instruction}
        {input} [/INST]

chat_template: llama3
tokens:
  - "[INST]"
  - " [/INST]"
  - "[QL]"
  - " [/QL]"
  - "[EXPLANATION]"
  - " [/EXPLANATION]"
# dataset formatting config

special_tokens:
  pad_token: <|end_of_text|>

val_set_size: 0.05

###
# Training Configuration
###

# masks the input messages so that the model learns and understands the language w/o being reliant on the input
train_on_inputs: false
# random seed for better reproducibility
seed: 117

# optimizer config
optimizer: adamw_bnb_8bit
learning_rate: 0.0001
lr_scheduler: cosine
num_epochs: 4
micro_batch_size: 4
gradient_accumulation_steps: 1
warmup_steps: 10

# axolotl saving config
dataset_prepared_path: last_run_prepared
output_dir: ./lora-out

# logging and eval config
logging_steps: 1
eval_steps: 0.05

# training performance optimization config
bf16: auto
tf32: false
gradient_checkpointing: true

###
# Miscellaneous Configuration
###

# when true, prevents over-writing the config from the CLI
strict: false

# "Don't mess with this, it's here for accelerate and torchrun" -- axolotl docs
local_rank:

# WANDB
wandb_mode:
wandb_project:
wandb_watch:
wandb_name:
wandb_run_id:

# Multi-GPU
# deepspeed: /root/axolotl/deepspeed_configs/zero3_bf16.json
# deepspeed: zero3_bf16.json
# deepspeed: /workspace/axolotl/deepspeed_configs/zero2.json
deepspeed:
fsdp:
fsdp_config:

```

</details><br>

# lora-out

This model is a fine-tuned version of [NousResearch/Hermes-3-Llama-3.1-8B](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0391

## 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: 117
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.1647        | 0.0769 | 1    | 2.2016          |
| 2.1505        | 0.2308 | 3    | 2.1168          |
| 1.7332        | 0.4615 | 6    | 1.5604          |
| 1.0807        | 0.6923 | 9    | 0.8788          |
| 0.5284        | 0.9231 | 12   | 0.4853          |
| 0.3215        | 1.1538 | 15   | 0.2911          |
| 0.2114        | 1.3846 | 18   | 0.1958          |
| 0.1493        | 1.6154 | 21   | 0.1374          |
| 0.1081        | 1.8462 | 24   | 0.1066          |
| 0.0751        | 2.0769 | 27   | 0.0821          |
| 0.0782        | 2.3077 | 30   | 0.0689          |
| 0.0524        | 2.5385 | 33   | 0.0602          |
| 0.0538        | 2.7692 | 36   | 0.0523          |
| 0.0442        | 3.0    | 39   | 0.0464          |
| 0.0385        | 3.2308 | 42   | 0.0417          |
| 0.0358        | 3.4615 | 45   | 0.0410          |
| 0.0336        | 3.6923 | 48   | 0.0388          |
| 0.0336        | 3.9231 | 51   | 0.0391          |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.20.0