---
library_name: peft
license: apache-2.0
base_model: unsloth/SmolLM-1.7B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: e5c7898a-4409-476c-b0e6-2048d1c3b9c8
  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
base_model: unsloth/SmolLM-1.7B-Instruct
bf16: true
chat_template: llama3
dataloader_num_workers: 6
dataset_prepared_path: null
datasets:
- data_files:
  - b4d50b4ebb62bd26_train_data.json
  ds_type: json
  format: custom
  path: /workspace/input_data/b4d50b4ebb62bd26_train_data.json
  type:
    field_instruction: instruction
    field_output: response
    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: 50
eval_table_size: null
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: true
hub_model_id: error577/e5c7898a-4409-476c-b0e6-2048d1c3b9c8
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.002
load_in_4bit: true
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 64
lora_dropout: 0.3
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 128
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 1000
auto_resume_from_checkpoints: true
micro_batch_size: 2
mlflow_experiment_name: /tmp/b4d50b4ebb62bd26_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 4
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: 50
sequence_len: 512
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.002
wandb_entity: null
wandb_mode: online
wandb_name: b8be9756-84be-4b64-aa93-937f8a9f4691
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: b8be9756-84be-4b64-aa93-937f8a9f4691
warmup_steps: 10
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# e5c7898a-4409-476c-b0e6-2048d1c3b9c8

This model is a fine-tuned version of [unsloth/SmolLM-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM-1.7B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7097

## 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: 0.002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 10
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.23          | 0.0000 | 1    | 1.0243          |
| 0.8101        | 0.0014 | 50   | 0.9230          |
| 0.6549        | 0.0028 | 100  | 1.0666          |
| 0.7171        | 0.0042 | 150  | 0.8552          |
| 0.606         | 0.0056 | 200  | 0.7939          |
| 0.5582        | 0.0069 | 250  | 0.7649          |
| 0.7431        | 0.0083 | 300  | 0.7490          |
| 0.7017        | 0.0097 | 350  | 0.7206          |
| 0.7743        | 0.0111 | 400  | 0.7006          |
| 0.507         | 0.0125 | 450  | 0.6939          |
| 0.5217        | 0.0139 | 500  | 0.6911          |
| 0.7122        | 0.0153 | 550  | 0.7409          |
| 0.6526        | 0.0167 | 600  | 0.7192          |
| 0.5694        | 0.0181 | 650  | 0.7097          |


### Framework versions

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