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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: arcee-ai/Virtuoso-Small |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- ToastyPigeon/some-rp |
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model-index: |
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- name: qwen-rp-test-h-qlora |
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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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# git clone https://github.com/axolotl-ai-cloud/axolotl |
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# cd axolotl |
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# git checkout 844331005c1ef45430ff26b9f42f757dce6ee66a |
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# pip3 install packaging ninja huggingface_hub[cli] |
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# pip3 install -e '.[flash-attn,deepspeed]' |
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# huggingface-cli login --token $hf_key && wandb login $wandb_key |
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# python -m axolotl.cli.preprocess nemo-rp-test-human.yml |
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# accelerate launch -m axolotl.cli.train qwen-rp-test-human.yml |
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# python -m axolotl.cli.merge_lora nemo-rp-test-human.yml |
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# huggingface-cli upload Columbidae/nemo-rp-test-human train-workspace/merged . --exclude "*.md" |
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# sleep 10h; runpodctl stop pod $RUNPOD_POD_ID & |
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# git clone https://github.com/axolotl-ai-cloud/axolotl && cd axolotl && pip3 install packaging ninja huggingface_hub[cli] && pip3 install -e '.[flash-attn,deepspeed]' && cd .. |
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# Model |
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base_model: arcee-ai/Virtuoso-Small |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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bf16: true |
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fp16: |
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tf32: false |
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flash_attention: true |
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special_tokens: |
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# Output |
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output_dir: ./train-workspace |
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hub_model_id: ToastyPigeon/qwen-rp-test-h-qlora |
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hub_strategy: "checkpoint" |
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auto_resume_from_checkpoint: true |
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#resume_from_checkpoint: ./train-workspace/checkpoint-304 |
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saves_per_epoch: 10 |
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save_total_limit: 3 |
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# Data |
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sequence_len: 8192 # fits |
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min_sample_len: 128 |
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chat_template: chatml |
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dataset_prepared_path: last_run_prepared |
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datasets: |
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- path: ToastyPigeon/some-rp |
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type: chat_template |
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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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warmup_steps: 20 |
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shuffle_merged_datasets: true |
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sample_packing: true |
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pad_to_sequence_len: true |
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# Batching |
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num_epochs: 1 |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 1 |
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eval_batch_size: 1 |
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# Evaluation |
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val_set_size: 80 |
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evals_per_epoch: 10 |
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eval_table_size: |
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eval_max_new_tokens: 256 |
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eval_sample_packing: false |
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save_safetensors: true |
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# WandB |
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wandb_project: Qwen-Rp-Test |
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#wandb_entity: |
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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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unsloth_cross_entropy_loss: 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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# LoRA |
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adapter: qlora |
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lora_r: 64 |
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lora_alpha: 128 |
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lora_dropout: 0.125 |
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lora_target_linear: true |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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lora_modules_to_save: |
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#peft_use_rslora: true |
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#loraplus_lr_ratio: 8 |
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# Optimizer |
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optimizer: paged_ademamix_8bit |
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lr_scheduler: cosine |
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learning_rate: 1e-4 |
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cosine_min_lr_ratio: 0.1 |
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weight_decay: 0.1 |
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max_grad_norm: 1.0 |
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# Misc |
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train_on_inputs: false |
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group_by_length: false |
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early_stopping_patience: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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debug: |
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json # previously blank |
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fsdp: |
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fsdp_config: |
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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_layer_norm: true |
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liger_glu_activation: true |
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liger_fused_linear_cross_entropy: true |
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gc_steps: 10 |
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# Debug config |
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debug: true |
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seed: 69 |
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``` |
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</details><br> |
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# qwen-rp-test-h-qlora |
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This model is a fine-tuned version of [arcee-ai/Virtuoso-Small](https://huggingface.co/arcee-ai/Virtuoso-Small) on the ToastyPigeon/some-rp dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3971 |
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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: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 69 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 8 |
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- optimizer: Use OptimizerNames.PAGED_ADEMAMIX_8BIT and the args are: |
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No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.4903 | 0.0026 | 1 | 2.5546 | |
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| 2.2882 | 0.1016 | 39 | 2.4302 | |
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| 2.3752 | 0.2031 | 78 | 2.4171 | |
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| 2.3249 | 0.3047 | 117 | 2.4119 | |
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| 2.2504 | 0.4062 | 156 | 2.4081 | |
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| 2.3905 | 0.5078 | 195 | 2.4030 | |
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| 2.3354 | 0.6094 | 234 | 2.4018 | |
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| 2.5473 | 0.7109 | 273 | 2.3996 | |
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| 2.4123 | 0.8125 | 312 | 2.3982 | |
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| 2.2878 | 0.9141 | 351 | 2.3971 | |
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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 |
