AlekseyKorshuk commited on
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End of training

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README.md ADDED
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+ ---
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+ license: bigcode-openrail-m
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+ base_model: WizardLM/WizardCoder-1B-V1.0
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+ tags:
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+ - axolotl
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+ - dpo
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+ - trl
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+ - dpo
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+ - generated_from_trainer
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+ model-index:
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+ - name: WizardCoder-1B-V1.0-dpo-beta-0.01
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+ results: []
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+ ---
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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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+
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+ [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.0`
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+ ```yaml
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+ base_model: WizardLM/WizardCoder-1B-V1.0
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+ trust_remote_code: true
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+
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+ hub_model_id: AlekseyKorshuk/WizardCoder-1B-V1.0-dpo-beta-0.01
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+ hub_strategy: every_save
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+
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+ load_in_8bit: false
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+ load_in_4bit: false
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+ strict: false
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+
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+ rl: dpo
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+ datasets:
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+ - path: AlekseyKorshuk/evol-codealpaca-v1-dpo
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+ split: train
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+ type: wizardcoder.intel
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+
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+
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+ dataset_prepared_path:
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+ #val_set_size: 0.001
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+ output_dir: ./output
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+
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+ sequence_len: 2048
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+ #sample_packing: false # currently unsupported
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+ pad_to_sequence_len:
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+
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+ lora_r:
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+ lora_alpha:
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+ lora_dropout:
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+ lora_target_modules:
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+ lora_target_linear:
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+ lora_fan_in_fan_out:
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+
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+ wandb_project: ui-thesis
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+ wandb_entity:
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+ wandb_watch:
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+ wandb_name: ultrachat-stable-code-3b-dpo-chatml-beta-0.01
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+ wandb_log_model:
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+
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+ gradient_accumulation_steps: 8
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+ micro_batch_size: 4
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+ num_epochs: 1
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+ optimizer: paged_adamw_8bit
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+ adam_beta1: 0.9
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+ adam_beta2: 0.95
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+ max_grad_norm: 1.0
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+ adam_epsilon: 0.00001
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+ lr_scheduler: cosine
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+ cosine_min_lr_ratio: 0.1
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+ learning_rate: 8.0e-7
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+ warmup_steps: 32
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+ #warmup_ratio: 0.1
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+ weight_decay: 0.01
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+ dpo_beta: 0.01
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: true
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+ fp16: false
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+ tf32: true
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+ #float16: true
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+
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+ gradient_checkpointing: true
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+ early_stopping_patience:
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+ resume_from_checkpoint:
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+ local_rank:
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+ logging_steps: 1
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+ xformers_attention:
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+ flash_attention: false
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+
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+
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+ #evals_per_epoch: 5
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+ #eval_table_size: 8 # Approximate number of predictions sent to wandb depending on batch size. Enabled above 0. Default is 0
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+ #eval_table_max_new_tokens: 768 # Total number of tokens generated for predictions sent to wandb. Default is 128
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+
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+ #chat_template: chatml
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+ #saves_per_epoch: 1
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+ save_steps: 500
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+ save_total_limit: 1
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+ seed: 42
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+ debug:
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+ deepspeed:
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+
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+
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+ fsdp:
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+ fsdp_config:
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+ resize_token_embeddings_to_32x: true
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+
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+ ```
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+
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+ </details><br>
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+
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+ # WizardCoder-1B-V1.0-dpo-beta-0.01
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+
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+ This model is a fine-tuned version of [WizardLM/WizardCoder-1B-V1.0](https://huggingface.co/WizardLM/WizardCoder-1B-V1.0) on the None dataset.
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 8e-07
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+ - train_batch_size: 4
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 32
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+ - training_steps: 312
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+
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+ ### Training results
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+
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.0.dev0
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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