Upload final fine-tuned Qwen3-0.6B model

README.md

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+---
+library_name: transformers
+base_model: timarni/qwen3_dpo
+tags:
+- generated_from_trainer
+datasets:
+- timarni/MNLP_intstruction_tuning
+model-index:
+- name: outputs/dpo_full_alpaca
+  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: timarni/qwen3_dpo
+# 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: timarni/MNLP_intstruction_tuning
+    type: alpaca
+    split: train
+
+shuffle_merged_datasets: true
+
+val_set_size: 0.1
+output_dir: ./outputs/dpo_full_alpaca
+dataset_prepared_path: last_run_prepared
+
+sequence_len: 4096 #2048
+sample_packing: true # was true -> need to check if it actually learns on the samples or not (better understand te hyperparam and event. install axolotl to debug)
+eval_sample_packing: true
+pad_to_sequence_len: true
+# train_on_inputs: true # NEW
+# group_by_length: false NEW?
+
+# To be sure that no LORA is done
+adapter: null
+lora: false
+merge_lora: false
+
+wandb_project: mnlp_project
+wandb_entity: tim-arni
+wandb_watch:
+wandb_name: dpo_full_alpaca_resume_from_ckpt
+wandb_log_model:
+
+gradient_accumulation_steps: 16 # 2
+micro_batch_size: 2 # 1
+num_epochs: 3
+optimizer: adamw_torch
+lr_scheduler: cosine
+learning_rate: 0.00005 # 0.00005
+# cosine_min_lr_ratio: 0.1
+
+warmup_ratio: 0.05
+weight_decay: 0.01
+
+bf16: auto
+tf32: true
+
+gradient_checkpointing: offload
+gradient_checkpointing_kwargs:
+  use_reentrant: false
+resume_from_checkpoint: /mloscratch/users/arni/Workspace/mnlp_sft/outputs/dpo_full_alpaca/checkpoint-186
+logging_steps: 1
+gradient_clipping: 1.0 # or max_grad_norm?
+flash_attention: true
+
+evals_per_epoch: 2
+saves_per_epoch: 1
+save_total_limit: 20
+special_tokens:
+
+```
+
+</details><br>
+
+# outputs/dpo_full_alpaca
+
+This model is a fine-tuned version of [timarni/qwen3_dpo](https://huggingface.co/timarni/qwen3_dpo) on the timarni/MNLP_intstruction_tuning dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1520
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- total_eval_batch_size: 8
+- 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: 13
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.7154        | 0.0107 | 1    | 1.1239          |
+| 0.1282        | 0.2567 | 24   | 0.2029          |
+| 0.1105        | 0.5134 | 48   | 0.1860          |
+| 0.1056        | 0.7701 | 72   | 0.1779          |
+| 0.1004        | 1.0214 | 96   | 0.1736          |
+| 0.0912        | 1.2781 | 120  | 0.1643          |
+| 0.0861        | 1.5348 | 144  | 0.1576          |
+| 0.0791        | 1.7914 | 168  | 0.1530          |
+| 0.0751        | 2.0642 | 192  | 0.1510          |
+| 0.0625        | 2.3209 | 216  | 0.1509          |
+| 0.0453        | 2.5775 | 240  | 0.1513          |
+| 0.0426        | 2.8342 | 264  | 0.1520          |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.5.1
+- Tokenizers 0.21.1

config.json

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 {
-  "_attn_implementation_autoset": true,
   "architectures": [
     "Qwen3ForCausalLM"
   ],

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.51.3"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:75f18bea40acac2a7ebd5f777510fde188f27ab48415502697db4590480c5a6e
+size 1192135096