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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: ibm-granite/granite-3.1-8b-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: granite-code-plans-3.1-8b-lora |
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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: `0.5.2` |
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```yaml |
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base_model: ibm-granite/granite-3.1-8b-instruct |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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resize_token_embeddings_to_32x: true |
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load_in_8bit: true |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: task_decomposition_training_data_code.jsonl |
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type: chat_template |
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chat_template: tokenizer_default |
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field_messages: conversations |
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message_field_role: role |
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message_field_content: value |
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dataset_prepared_path: last_run_prepared_sft |
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val_set_size: 0 |
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sequence_len: 8192 |
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sample_packing: false |
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pad_to_sequence_len: true |
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eval_sample_packing: false |
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output_dir: granite-code-plans-3.1-8b-lora |
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wandb_project: null |
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wandb_entity: null |
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wandb_watch: null |
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wandb_name: null |
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wandb_log_model: null |
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adapter: lora |
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lora_model_dir: |
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lora_r: 32 |
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lora_alpha: 16 |
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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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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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eval_batch_size: 1 |
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num_epochs: 3 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 1e-05 |
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max_grad_norm: 1.0 |
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logging_steps: 10 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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xformers_attention: |
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flash_attention: true |
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warmup_ratio: 0.05 |
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eval_steps: |
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save_strategy: epoch |
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eval_table_size: |
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num_processes: 8 |
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deepspeed: |
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weight_decay: 0.0 |
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``` |
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</details><br> |
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# home/ec2-user/SageMaker/task_decomposition/trained_models/granite-code-plans-3.1-8b-lora |
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This model is a fine-tuned version of [ibm-granite/granite-3.1-8b-instruct](https://huggingface.co/ibm-granite/granite-3.1-8b-instruct) on the task_decomposition_training_data_code.jsonl 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: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 8 |
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- optimizer: Use adamw_bnb_8bit 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: 131 |
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- num_epochs: 3 |
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### Training results |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.46.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
