---
library_name: peft
license: apache-2.0
base_model: EleutherAI/pythia-160m
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 1049f57e-4e7b-4d20-8524-075e12b98361
  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: EleutherAI/pythia-160m
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
  - cabe0edc52f1824b_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/cabe0edc52f1824b_train_data.json
  type:
    field_input: policy
    field_instruction: redteam_query
    field_output: jailbreak_query
    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: 3
eval_batch_size: 4
eval_max_new_tokens: 128
eval_steps: 200
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: true
hub_model_id: great0001/1049f57e-4e7b-4d20-8524-075e12b98361
hub_strategy: end
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 50
lora_alpha: 64
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 32
lora_target_linear: true
lr_scheduler: constant
max_grad_norm: 1.0
max_memory:
  0: 75GB
max_steps: 17977
micro_batch_size: 4
mlflow_experiment_name: /tmp/cabe0edc52f1824b_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 10
optim_args:
  adam_beta1: 0.9
  adam_beta2: 0.95
  adam_epsilon: 1e-5
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 200
saves_per_epoch: null
sequence_len: 512
special_tokens:
  pad_token: <|endoftext|>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 2677b7fe-e0a2-439d-a729-54f9c5263ad0
wandb_project: SN56-33
wandb_run: your_name
wandb_runid: 2677b7fe-e0a2-439d-a729-54f9c5263ad0
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 1049f57e-4e7b-4d20-8524-075e12b98361

This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3410

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 50
- training_steps: 16614

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0006 | 1    | 5.0096          |
| 19.4463       | 0.1204 | 200  | 5.1624          |
| 16.3716       | 0.2407 | 400  | 3.9670          |
| 15.4725       | 0.3611 | 600  | 4.3231          |
| 13.6185       | 0.4815 | 800  | 4.5737          |
| 13.2182       | 0.6019 | 1000 | 3.3886          |
| 11.9674       | 0.7222 | 1200 | 3.3497          |
| 11.3688       | 0.8426 | 1400 | 3.2310          |
| 12.5514       | 0.9630 | 1600 | 3.9830          |
| 10.2903       | 1.0835 | 1800 | 2.4156          |
| 8.989         | 1.2039 | 2000 | 2.3129          |
| 9.2686        | 1.3243 | 2200 | 2.4183          |
| 9.0286        | 1.4446 | 2400 | 2.4323          |
| 9.8924        | 1.5650 | 2600 | 2.3410          |


### Framework versions

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