---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen3-0.6B-Base
tags:
- generated_from_trainer
datasets:
- timarni/s1k_r1_clean
model-index:
- name: outputs/qwen3_s1k
  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: `0.9.2`
```yaml
base_model: Qwen/Qwen3-0.6B-Base
# Automatically upload checkpoint and final model to HF
# hub_model_id: username/custom_model_name

plugins:
  - axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
strict: false

chat_template: qwen3
datasets:
  - path: /mloscratch/users/arni/Workspace/mnlp_sft/datasets/s1k.json
    type: chat_template
    split: train
    field_messages: conversations
    # message_property_mappings:
    #   role: from
    #   content: value

output_dir: ./outputs/qwen3_s1k
dataset_prepared_path: last_run_prepared

# To be sure that no LORA is done
adapter: null
lora: false
merge_lora: false

sequence_len: 4096 #2048
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

wandb_project: mnlp_project
wandb_entity: tim-arni
wandb_watch:
wandb_name: qwen3_s1k
wandb_log_model:

gradient_accumulation_steps: 2 # 16 following https://unsloth.ai/blog/qwen3
micro_batch_size: 1 # 2
num_epochs: 5
optimizer: adamw_torch
lr_scheduler: cosine
learning_rate: 0.00005 # 0.0002
cosine_min_lr_ratio: 0.1

bf16: auto
tf32: true

gradient_checkpointing: offload
gradient_checkpointing_kwargs:
  use_reentrant: false
resume_from_checkpoint:
logging_steps: 1
gradient_clipping: 1.0
flash_attention: true

warmup_ratio: 0.03
evals_per_epoch: 4
saves_per_epoch: 1
weight_decay: 1e-4
special_tokens:

```

</details><br>

# outputs/qwen3_s1k

This model is a fine-tuned version of [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) on the /mloscratch/users/arni/Workspace/mnlp_sft/datasets/s1k.json dataset.

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Use adamw_torch 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: 6
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.51.3
- Pytorch 2.5.1+cu121
- Datasets 3.5.1
- Tokenizers 0.21.1