End of training
Browse files- README.md +162 -0
- pytorch_model.bin +3 -0
README.md
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---
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license: llama2
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library_name: peft
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tags:
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- axolotl
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- dpo
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- trl
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- generated_from_trainer
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base_model: codellama/CodeLlama-7b-hf
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model-index:
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- name: modeltest1-dpo
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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/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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axolotl version: `0.4.0`
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```yaml
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base_model: codellama/CodeLlama-7b-hf
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model_type: LlamaForCausalLM
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tokenizer_type: CodeLlamaTokenizer
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is_llama_derived_model: true
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hub_model_id: noeloco/modeltest1-dpo
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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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datasets:
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- path: noeloco/fizzbuzz-sft
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type: alpaca
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ds_type: json
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hf_use_auth_token: true
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push_dataset_to_hub: noeloco
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val_set_size: 0.05
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output_dir: ./lora-out
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chat_template: chatml
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rl: dpo
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datasets:
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- path: noeloco/fizzbuzz-dpo
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split: train
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data_files:
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- /tmp/fizzbuzz-ft/datasets/training-set-dpo.json
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#type:
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# field_prompt: question
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# field_chosen: chosen
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# field_rejected: rejected
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ds_type: json
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#type: intel_apply_chatml
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type: chatml.intel
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hf_use_auth_token: true
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push_dataset_to_hub: noeloco
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val_set_size: 0.05
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output_dir: ./lora-out
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chat_template: chatml
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sequence_len: 2048
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sample_packing: false
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pad_to_sequence_len: true
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adapter: lora
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lora_model_dir:
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lora_r: 16
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lora_alpha: 8
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lora_dropout: 0.05
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lora_target_linear: true
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lora_fan_in_fan_out:
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wandb_project: runpod1
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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:
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gradient_accumulation_steps: 1
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micro_batch_size: 2
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num_epochs: 3
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optimizer: paged_adamw_32bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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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: false
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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: true
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warmup_steps: 10
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evals_per_epoch: 4
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saves_per_epoch: 1
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debug: true
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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bos_token: "<s>"
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eos_token: "</s>"
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unk_token: "<unk>"
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```
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</details><br>
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# modeltest1-dpo
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This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None 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: 0.0002
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 10
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- training_steps: 222
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### Training results
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### Framework versions
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- PEFT 0.10.1.dev0
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- Transformers 4.40.0.dev0
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- Pytorch 2.1.2+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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pytorch_model.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:a2d4c0977c02e5eb8499d5e9d472853fe43fa4bbc11226f37b157a77b4674b08
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size 4248847729
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