---
library_name: peft
license: apache-2.0
base_model: unsloth/gemma-1.1-2b-it
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 0fbfb23b-c3ed-4087-9035-12ed75edce4a
  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
auto_resume_from_checkpoints: true
base_model: unsloth/gemma-1.1-2b-it
bf16: auto
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 6
datasets:
- data_files:
  - 8b5afe50837b255a_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/8b5afe50837b255a_train_data.json
  type:
    field_input: distractor-0
    field_instruction: startphrase
    field_output: gold-ending
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 3
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: true
group_by_length: false
hub_model_id: error577/0fbfb23b-c3ed-4087-9035-12ed75edce4a
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: 1
lora_alpha: 64
lora_dropout: 0.1
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: 4
mlflow_experiment_name: /tmp/8b5afe50837b255a_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 3
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
sequence_len: 256
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: 628eefeb-6b62-454a-9537-12242629b85d
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 628eefeb-6b62-454a-9537-12242629b85d
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# 0fbfb23b-c3ed-4087-9035-12ed75edce4a

This model is a fine-tuned version of [unsloth/gemma-1.1-2b-it](https://huggingface.co/unsloth/gemma-1.1-2b-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6509

## 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=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 30
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 5.9428        | 0.0002 | 1    | 6.1052          |
| 2.5262        | 0.0347 | 200  | 2.7630          |
| 2.956         | 0.0693 | 400  | 2.7125          |
| 2.7371        | 0.1040 | 600  | 2.7114          |
| 2.7291        | 0.1387 | 800  | 2.6787          |
| 2.9438        | 0.1734 | 1000 | 2.6667          |
| 2.5104        | 0.2080 | 1200 | 2.6644          |
| 2.2874        | 0.2427 | 1400 | 2.6748          |
| 2.5989        | 0.2774 | 1600 | 2.6692          |
| 2.7873        | 0.3121 | 1800 | 2.6559          |
| 2.742         | 0.3467 | 2000 | 2.6614          |
| 2.8575        | 0.3814 | 2200 | 2.6694          |
| 2.4323        | 0.4161 | 2400 | 2.6472          |
| 2.6942        | 0.4508 | 2600 | 2.6358          |
| 2.5881        | 0.4854 | 2800 | 2.6310          |
| 3.1393        | 0.5201 | 3000 | 2.6596          |
| 2.943         | 0.5548 | 3200 | 2.6602          |
| 2.6964        | 0.5895 | 3400 | 2.6509          |


### Framework versions

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