---
library_name: peft
base_model: rayonlabs/83847950-33bc-4506-ba82-48653a06540a
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 81e8adf2-9dfa-4f49-bd89-57c64afb2de4
  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: rayonlabs/83847950-33bc-4506-ba82-48653a06540a
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - f4b7f90f2a0ae91e_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/f4b7f90f2a0ae91e_train_data.json
  type:
    field_input: context
    field_instruction: question
    field_output: final_decision
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
device_map: auto
do_eval: true
early_stopping_patience: 5
eval_batch_size: 4
eval_max_new_tokens: 128
eval_steps: 150
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 1
gradient_checkpointing: false
group_by_length: false
hub_model_id: auxyus/81e8adf2-9dfa-4f49-bd89-57c64afb2de4
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 4.4e-05
load_in_4bit: false
load_in_8bit: false
local_rank: 0
logging_steps: 10
lora_alpha: 32
lora_dropout: 0.2
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine_with_restarts
max_grad_norm: 1.0
max_memory:
  0: 75GB
max_steps: 600
micro_batch_size: 4
mlflow_experiment_name: /tmp/f4b7f90f2a0ae91e_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.999
  adam_epsilon: 1e-08
optimizer: adamw_torch
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 150
save_total_limit: 1
saves_per_epoch: null
sequence_len: 512
special_tokens:
  pad_token: <|end_of_text|>
strict: false
tf32: null
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: acopia-grant
wandb_mode: online
wandb_name: 53e001ba-f4ae-454f-a837-80c11f92d62b
wandb_project: Gradients-On-2
wandb_run: your_name
wandb_runid: 53e001ba-f4ae-454f-a837-80c11f92d62b
warmup_ratio: 0.1
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 81e8adf2-9dfa-4f49-bd89-57c64afb2de4

This model is a fine-tuned version of [rayonlabs/83847950-33bc-4506-ba82-48653a06540a](https://huggingface.co/rayonlabs/83847950-33bc-4506-ba82-48653a06540a) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0464

## 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: 4.4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.999,adam_epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 60
- training_steps: 600

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0000 | 1    | 2.0931          |
| 0.031         | 0.0030 | 150  | 0.0823          |
| 0.0013        | 0.0060 | 300  | 0.0778          |
| 0.0107        | 0.0090 | 450  | 0.0482          |
| 0.0833        | 0.0120 | 600  | 0.0464          |


### Framework versions

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