---
library_name: peft
license: bigcode-openrail-m
base_model: bigcode/starcoder2-3b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: a0abd2fc-0e9c-4a53-83bd-5435c4990984
  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: bigcode/starcoder2-3b
bf16: auto
chat_template: llama3
dataset_prepared_path: null
dataset_processes: 6
datasets:
- data_files:
  - ad8f783c2fd92065_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/ad8f783c2fd92065_train_data.json
  type:
    field_input: span_labels
    field_instruction: source_text
    field_output: target_text
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: 5
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: 8
gradient_checkpointing: true
group_by_length: false
hub_model_id: error577/a0abd2fc-0e9c-4a53-83bd-5435c4990984
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: 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: 2
mlflow_experiment_name: /tmp/ad8f783c2fd92065_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: 512
special_tokens:
  pad_token: <|endoftext|>
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: 2807bbf9-436c-4c90-b92a-3dbfd7f919cd
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 2807bbf9-436c-4c90-b92a-3dbfd7f919cd
warmup_steps: 30
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# a0abd2fc-0e9c-4a53-83bd-5435c4990984

This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0052

## 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: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 18.6994       | 0.0001 | 1    | 0.3745          |
| 0.3429        | 0.0143 | 200  | 0.0124          |
| 0.1255        | 0.0287 | 400  | 0.0100          |
| 0.5354        | 0.0430 | 600  | 0.0093          |
| 0.1077        | 0.0573 | 800  | 0.0069          |
| 0.1981        | 0.0717 | 1000 | 0.0083          |
| 0.0596        | 0.0860 | 1200 | 0.0060          |
| 0.0976        | 0.1003 | 1400 | 0.0060          |
| 0.0257        | 0.1147 | 1600 | 0.0061          |
| 0.0718        | 0.1290 | 1800 | 0.0059          |
| 0.1601        | 0.1433 | 2000 | 0.0063          |
| 0.0453        | 0.1576 | 2200 | 0.0051          |
| 0.1005        | 0.1720 | 2400 | 0.0055          |
| 0.1717        | 0.1863 | 2600 | 0.0053          |
| 0.0081        | 0.2006 | 2800 | 0.0054          |
| 0.0468        | 0.2150 | 3000 | 0.0055          |
| 0.0827        | 0.2293 | 3200 | 0.0052          |


### Framework versions

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