---
library_name: peft
base_model: trl-internal-testing/tiny-random-LlamaForCausalLM
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 345fef6a-8237-4ee7-82b7-ba614660cdd1
  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: trl-internal-testing/tiny-random-LlamaForCausalLM
bf16: true
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - 570f06fa330a02a8_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/570f06fa330a02a8_train_data.json
  type:
    field_input: starter_code
    field_instruction: question_content
    field_output: test
    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: mamung/345fef6a-8237-4ee7-82b7-ba614660cdd1
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/570f06fa330a02a8_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
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: eddysang
wandb_mode: online
wandb_name: 835a7d05-70b3-4946-9a54-04ee779c4f19
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 835a7d05-70b3-4946-9a54-04ee779c4f19
warmup_steps: 20
weight_decay: 0.02
xformers_attention: false

```

</details><br>

# 345fef6a-8237-4ee7-82b7-ba614660cdd1

This model is a fine-tuned version of [trl-internal-testing/tiny-random-LlamaForCausalLM](https://huggingface.co/trl-internal-testing/tiny-random-LlamaForCausalLM) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 10.2883

## 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: 86

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0350 | 1    | 10.3792         |
| 10.3758       | 0.2801 | 8    | 10.3774         |
| 10.3712       | 0.5602 | 16   | 10.3714         |
| 10.3635       | 0.8403 | 24   | 10.3584         |
| 13.5544       | 1.1368 | 32   | 10.3373         |
| 10.2418       | 1.4168 | 40   | 10.3136         |
| 10.2948       | 1.6969 | 48   | 10.2994         |
| 10.258        | 1.9770 | 56   | 10.2935         |
| 10.1202       | 2.2735 | 64   | 10.2904         |
| 10.3454       | 2.5536 | 72   | 10.2889         |
| 10.0236       | 2.8337 | 80   | 10.2883         |


### Framework versions

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