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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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+ license: llama2
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+ library_name: peft
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ base_model: codellama/CodeLlama-7b-Instruct-hf
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+ model-index:
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+ - name: taopanda-3_b82cc4a3-a6de-4f53-a886-01e75f988ae4
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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: `0.4.1`
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+ ```yaml
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+ adapter: lora
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+ base_model: codellama/CodeLlama-7b-Instruct-hf
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+ bf16: auto
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+ datasets:
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+ - data_files:
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+ - 08fb4954d2e54910_train_data.json
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+ ds_type: json
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+ format: custom
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+ path: 08fb4954d2e54910_train_data.json
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+ type:
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+ field: null
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+ field_input: null
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+ field_instruction: prompt
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+ field_output: chosen
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+ field_system: null
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+ format: null
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+ no_input_format: null
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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: null
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+ eval_max_new_tokens: 128
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+ eval_sample_packing: false
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+ eval_table_size: null
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+ evals_per_epoch: 4
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+ flash_attention: true
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+ fp16: null
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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: false
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+ hub_model_id: FatCat87/taopanda-3_b82cc4a3-a6de-4f53-a886-01e75f988ae4
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+ learning_rate: 0.0002
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+ load_in_4bit: false
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+ load_in_8bit: true
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+ local_rank: null
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+ logging_steps: 1
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+ lora_alpha: 16
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+ lora_dropout: 0.05
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+ lora_r: 32
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+ lora_target_linear: true
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+ lr_scheduler: cosine
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+ micro_batch_size: 2
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+ model_type: AutoModelForCausalLM
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+ num_epochs: 2
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+ optimizer: adamw_bnb_8bit
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+ output_dir: ./outputs/out/taopanda-3_b82cc4a3-a6de-4f53-a886-01e75f988ae4
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+ pad_to_sequence_len: true
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+ resume_from_checkpoint: null
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+ sample_packing: true
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+ saves_per_epoch: 1
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+ seed: 37417
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+ sequence_len: 4096
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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: 0.1
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+ wandb_entity: fatcat87-taopanda
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+ wandb_log_model: null
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+ wandb_mode: online
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+ wandb_name: taopanda-3_b82cc4a3-a6de-4f53-a886-01e75f988ae4
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+ wandb_project: subnet56
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+ wandb_runid: taopanda-3_b82cc4a3-a6de-4f53-a886-01e75f988ae4
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+ wandb_watch: null
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+ warmup_ratio: 0.05
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+ weight_decay: 0.0
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+ xformers_attention: null
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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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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fatcat87-taopanda/subnet56/runs/mvlfr6qs)
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+ # taopanda-3_b82cc4a3-a6de-4f53-a886-01e75f988ae4
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+
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+ This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0467
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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: 37417
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 8
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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: 5
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+ - num_epochs: 2
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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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+ | 0.1412 | 0.0157 | 1 | 0.1613 |
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+ | 0.0635 | 0.2520 | 16 | 0.0658 |
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+ | 0.0459 | 0.5039 | 32 | 0.0561 |
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+ | 0.0453 | 0.7559 | 48 | 0.0522 |
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+ | 0.0483 | 1.0079 | 64 | 0.0497 |
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+ | 0.0366 | 1.2323 | 80 | 0.0483 |
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+ | 0.0408 | 1.4843 | 96 | 0.0472 |
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+ | 0.0363 | 1.7362 | 112 | 0.0467 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.42.3
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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