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---
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library_name: peft
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license: apache-2.0
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base_model: Qwen/Qwen2.5-32B-Instruct
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tags:
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- generated_from_trainer
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datasets:
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- Fizzarolli/inkmix-v2
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language:
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- zho
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- eng
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- fra
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- spa
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- por
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- deu
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- ita
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- rus
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- jpn
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- kor
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- vie
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- tha
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- ara
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model-index:
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- name: ckpts
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<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)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.6.0`
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```yaml
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base_model: Qwen/Qwen2.5-32B-Instruct
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load_in_8bit: true
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load_in_4bit: false
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_glu_activation: true
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liger_fused_linear_cross_entropy: true
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#unsloth_lora_mlp: true
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#unsloth_lora_qkv: true
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#unsloth_lora_o: true
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strict: false
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adapter: lora
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lora_r: 16
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lora_alpha: 32
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lora_dropout: 0.25
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lora_target_linear: true
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peft_layers_to_transform:
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loraplus_lr_ratio: 16
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chat_template: chatml
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datasets:
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- path: Fizzarolli/inkmix-v2
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type: chat_template
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chat_template: tokenizer_default
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split: train
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field_messages: conversations
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message_field_role: from
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message_field_content: value
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dataset_prepared_path: last_run_prepared
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#val_set_size: 0.02
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output_dir: ./ckpts
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sequence_len: 8192
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sample_packing: true
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pad_to_sequence_len: true
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#wandb_project: teleut-7b-rp
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#wandb_entity:
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#wandb_watch:
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#wandb_name:
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#wandb_log_model: checkpoint
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# mlflow configuration if you're using it
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mlflow_tracking_uri: https://public-tracking.mlflow-e00zzfjq11ky6jcgtv.backbone-e00bgn6e63256prmhq.msp.eu-north1.nebius.cloud
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mlflow_experiment_name: tq-32b-rp-inkmixv2
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mlflow_run_name: v1
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hf_mlflow_log_artifacts: true
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gradient_accumulation_steps: 2
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micro_batch_size: 8
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num_epochs: 2
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 6e-5
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train_on_inputs: false
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group_by_length: false
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bf16: auto
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fp16:
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tf32: false
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gradient_checkpointing: unsloth
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gradient_checkpointing_kwargs:
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use_reentrant: false
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early_stopping_patience:
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resume_from_checkpoint:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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#deepspeed: deepspeed_configs/zero3_bf16.json
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warmup_steps: 25
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#evals_per_epoch: 4
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eval_table_size:
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saves_per_epoch: 10
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debug:
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weight_decay: 0.05
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```
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</details><br>
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# ckpts
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This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) on the Fizzarolli/inkmix-v2 dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 6e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 25
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- num_epochs: 2
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### Training results
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### Framework versions
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- PEFT 0.14.0
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- Transformers 4.47.1
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.21.0 |
