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End of training

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  2. adapter_model.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: peft
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+ base_model: Korabbit/llama-2-ko-7b
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ model-index:
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+ - name: 352cbfe1-34a5-448e-9702-bb0ff1c2125b
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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/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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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ adapter: lora
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+ base_model: Korabbit/llama-2-ko-7b
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+ bf16: auto
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+ chat_template: llama3
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+ dataset_prepared_path: null
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+ datasets:
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+ - data_files:
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+ - d6b44a0c297f4d53_train_data.json
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+ ds_type: json
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+ format: custom
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+ path: /workspace/input_data/d6b44a0c297f4d53_train_data.json
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+ type:
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+ field_input: disease
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+ field_instruction: catalyst
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+ field_output: stage
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+ format: '{instruction} {input}'
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+ no_input_format: '{instruction}'
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+ system_format: '{system}'
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+ system_prompt: ''
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+ debug: null
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+ deepspeed: null
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+ early_stopping_patience: 1
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+ eval_max_new_tokens: 128
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+ eval_steps: 50
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+ eval_table_size: null
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+ flash_attention: true
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+ fp16: false
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+ fsdp: null
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+ fsdp_config: null
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+ gradient_accumulation_steps: 4
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+ gradient_checkpointing: true
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+ group_by_length: true
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+ hub_model_id: diaenra/352cbfe1-34a5-448e-9702-bb0ff1c2125b
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+ hub_repo: null
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+ hub_strategy: checkpoint
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+ hub_token: null
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+ learning_rate: 0.0002
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+ load_in_4bit: false
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+ load_in_8bit: false
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+ local_rank: null
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+ logging_steps: 1
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+ lora_alpha: 32
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+ lora_dropout: 0.05
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+ lora_fan_in_fan_out: null
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+ lora_model_dir: null
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+ lora_r: 16
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+ lora_target_linear: true
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+ lr_scheduler: cosine
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+ max_steps: 100
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+ micro_batch_size: 2
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+ mlflow_experiment_name: /tmp/d6b44a0c297f4d53_train_data.json
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+ model_type: AutoModelForCausalLM
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+ num_epochs: 3
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+ optimizer: adamw_torch
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+ output_dir: miner_id_24
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+ pad_to_sequence_len: true
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+ resume_from_checkpoint: null
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+ s2_attention: null
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+ sample_packing: false
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+ save_steps: 50
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+ sequence_len: 4056
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+ special_tokens:
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+ pad_token: </s>
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+ strict: false
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+ tf32: false
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+ tokenizer_type: AutoTokenizer
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+ train_on_inputs: false
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+ trust_remote_code: true
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+ val_set_size: 0.05
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+ wandb_entity: diaenra-tao-miner
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+ wandb_mode: online
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+ wandb_name: 352cbfe1-34a5-448e-9702-bb0ff1c2125b
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+ wandb_project: tao
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+ wandb_run: diaenra
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+ wandb_runid: 352cbfe1-34a5-448e-9702-bb0ff1c2125b
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+ warmup_ratio: 0.05
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+ weight_decay: 0.01
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+ xformers_attention: 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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+ # 352cbfe1-34a5-448e-9702-bb0ff1c2125b
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+
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+ This model is a fine-tuned version of [Korabbit/llama-2-ko-7b](https://huggingface.co/Korabbit/llama-2-ko-7b) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1236
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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: 0.0002
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 8
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH 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: 5
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+ - training_steps: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 3.0591 | 0.0025 | 1 | 3.5778 |
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+ | 0.009 | 0.1267 | 50 | 0.1396 |
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+ | 0.0033 | 0.2533 | 100 | 0.1236 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.46.0
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+ - Pytorch 2.5.0+cu124
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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