---
library_name: peft
base_model: unsloth/Hermes-3-Llama-3.1-8B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 86b78a72-7e39-408d-a5a1-39422ed40ff5
  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/Hermes-3-Llama-3.1-8B
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 044fd24ccc165951_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/044fd24ccc165951_train_data.json
  type:
    field_instruction: question
    field_output: answer
    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: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
gradient_clipping: 1.0
group_by_length: false
hub_model_id: Nexspear/86b78a72-7e39-408d-a5a1-39422ed40ff5
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 5.0e-05
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 3
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_steps: 100
micro_batch_size: 8
mlflow_experiment_name: /tmp/044fd24ccc165951_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
saves_per_epoch: 4
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: techspear-hub
wandb_mode: online
wandb_name: f86da2b3-43cf-4a85-a75e-4ff1c4628088
wandb_project: Gradients-On-Four
wandb_run: your_name
wandb_runid: f86da2b3-43cf-4a85-a75e-4ff1c4628088
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 86b78a72-7e39-408d-a5a1-39422ed40ff5

This model is a fine-tuned version of [unsloth/Hermes-3-Llama-3.1-8B](https://huggingface.co/unsloth/Hermes-3-Llama-3.1-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3427

## 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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0033 | 1    | 2.4745          |
| 2.2337        | 0.0299 | 9    | 2.3853          |
| 1.9607        | 0.0599 | 18   | 1.7930          |
| 1.4597        | 0.0898 | 27   | 1.4339          |
| 1.2824        | 0.1197 | 36   | 1.3913          |
| 1.2844        | 0.1496 | 45   | 1.3703          |
| 1.4073        | 0.1796 | 54   | 1.3600          |
| 1.374         | 0.2095 | 63   | 1.3521          |
| 1.2855        | 0.2394 | 72   | 1.3468          |
| 1.3598        | 0.2693 | 81   | 1.3438          |
| 1.312         | 0.2993 | 90   | 1.3431          |
| 1.4346        | 0.3292 | 99   | 1.3427          |


### Framework versions

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