---
library_name: peft
license: llama3.2
base_model: NousResearch/Llama-3.2-1B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 6a8050fe-e245-4bf5-92c6-2239194b4225
  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: NousResearch/Llama-3.2-1B
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - fffa53a70b34ee7a_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/fffa53a70b34ee7a_train_data.json
  type:
    field_input: section_names
    field_instruction: article
    field_output: abstract
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 256
eval_table_size: null
evals_per_epoch: 4
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 32
gradient_checkpointing: true
group_by_length: false
hub_model_id: eddysang/6a8050fe-e245-4bf5-92c6-2239194b4225
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 3
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lora_target_modules:
- q_proj
- k_proj
- v_proj
- o_proj
lr_scheduler: cosine
max_grad_norm: 2
max_steps: 100
micro_batch_size: 2
mlflow_experiment_name: /tmp/fffa53a70b34ee7a_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1.0e-05
optimizer: adamw_torch
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: 2048
special_tokens:
  pad_token: <|end_of_text|>
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: yaudayah0
wandb_mode: online
wandb_name: 3276fb8f-c293-4b62-9f20-ac5afd3074e1
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 3276fb8f-c293-4b62-9f20-ac5afd3074e1
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false

```

</details><br>

# 6a8050fe-e245-4bf5-92c6-2239194b4225

This model is a fine-tuned version of [NousResearch/Llama-3.2-1B](https://huggingface.co/NousResearch/Llama-3.2-1B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4919

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- training_steps: 100

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0016 | 1    | 1.8242          |
| 1.6705        | 0.0141 | 9    | 1.6580          |
| 1.6546        | 0.0282 | 18   | 1.5876          |
| 1.5261        | 0.0424 | 27   | 1.5503          |
| 1.4369        | 0.0565 | 36   | 1.5314          |
| 1.5643        | 0.0706 | 45   | 1.5160          |
| 1.4754        | 0.0847 | 54   | 1.5080          |
| 1.4584        | 0.0988 | 63   | 1.5008          |
| 1.4337        | 0.1129 | 72   | 1.4967          |
| 1.5454        | 0.1271 | 81   | 1.4935          |
| 1.4752        | 0.1412 | 90   | 1.4923          |
| 1.4875        | 0.1553 | 99   | 1.4919          |


### Framework versions

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