---
library_name: peft
license: apache-2.0
base_model: OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
tags:
- axolotl
- generated_from_trainer
model-index:
- name: f6e5e65a-341f-40c5-9e3f-873cee5c85ac
  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: qlora
auto_resume_from_checkpoints: true
base_model: OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5
bf16: auto
chat_template: llama3
dataloader_num_workers: 12
dataset_prepared_path: null
datasets:
- data_files:
  - 05eaf15988462a86_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/05eaf15988462a86_train_data.json
  type:
    field_instruction: question
    field_output: query
    format: '{instruction}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 100
eval_table_size: null
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: error577/f6e5e65a-341f-40c5-9e3f-873cee5c85ac
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 10
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: cosine
max_grad_norm: 1.0
max_steps: null
micro_batch_size: 1
mlflow_experiment_name: /tmp/05eaf15988462a86_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
optimizer: adamw_torch_4bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 100
sequence_len: 128
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.005
wandb_entity: null
wandb_mode: online
wandb_name: 1a9999e5-c0b6-4897-81e0-b48135a42da3
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 1a9999e5-c0b6-4897-81e0-b48135a42da3
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# f6e5e65a-341f-40c5-9e3f-873cee5c85ac

This model is a fine-tuned version of [OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5082

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_4BIT 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: 30
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0006 | 1    | 2.8643          |
| 3.9097        | 0.0572 | 100  | 0.7509          |
| 2.1421        | 0.1143 | 200  | 0.7648          |
| 2.7715        | 0.1715 | 300  | 0.6629          |
| 1.8035        | 0.2286 | 400  | 0.5600          |
| 1.9732        | 0.2858 | 500  | 0.6014          |
| 2.6536        | 0.3430 | 600  | 0.4555          |
| 1.6998        | 0.4001 | 700  | 0.4196          |
| 1.4222        | 0.4573 | 800  | 0.4635          |
| 1.6247        | 0.5144 | 900  | 0.4698          |
| 2.3622        | 0.5716 | 1000 | 0.5082          |


### Framework versions

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