End of training

README.md

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+---
+library_name: peft
+base_model: NousResearch/CodeLlama-7b-hf-flash
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: c652616d-b61a-42ad-99f7-0902847573e6
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+adapter: lora
+base_model: NousResearch/CodeLlama-7b-hf-flash
+bf16: auto
+chat_template: llama3
+cosine_min_lr_ratio: 0.1
+data_processes: 16
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - 9a604e0f48f65751_train_data.json
+  ds_type: json
+  field: text
+  path: /workspace/input_data/9a604e0f48f65751_train_data.json
+  type: completion
+debug: null
+deepspeed: null
+device_map: auto
+do_eval: true
+eval_batch_size: 1
+eval_sample_packing: false
+eval_steps: 25
+evaluation_strategy: steps
+flash_attention: false
+fp16: null
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 32
+gradient_checkpointing: true
+group_by_length: true
+hub_model_id: dada22231/c652616d-b61a-42ad-99f7-0902847573e6
+hub_strategy: checkpoint
+hub_token: null
+hub_username: dada22231
+learning_rate: 0.0001
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: 1
+lora_alpha: 64
+lora_dropout: 0.05
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 32
+lora_target_linear: true
+lora_target_modules:
+- q_proj
+- v_proj
+lr_scheduler: cosine
+max_grad_norm: 1.0
+max_memory:
+  0: 70GiB
+  1: 70GiB
+  2: 70GiB
+  3: 70GiB
+max_steps: 50
+micro_batch_size: 1
+mlflow_experiment_name: /tmp/9a604e0f48f65751_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 3
+optim_args:
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_epsilon: 1e-5
+optimizer: adamw_torch
+output_dir: miner_id_24
+pad_to_sequence_len: true
+repository_id: dada22231/c652616d-b61a-42ad-99f7-0902847573e6
+resume_from_checkpoint: null
+s2_attention: null
+sample_packing: false
+save_steps: 25
+save_strategy: steps
+sequence_len: 2048
+strict: false
+tf32: false
+tokenizer_type: AutoTokenizer
+torch_compile: false
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 50
+wandb_entity: null
+wandb_mode: online
+wandb_name: c652616d-b61a-42ad-99f7-0902847573e6
+wandb_project: Public_TuningSN
+wandb_runid: c652616d-b61a-42ad-99f7-0902847573e6
+warmup_ratio: 0.04
+weight_decay: 0.01
+xformers_attention: null
+
+```
+
+</details><br>
+
+# c652616d-b61a-42ad-99f7-0902847573e6
+
+This model is a fine-tuned version of [NousResearch/CodeLlama-7b-hf-flash](https://huggingface.co/NousResearch/CodeLlama-7b-hf-flash) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.6576
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 128
+- total_eval_batch_size: 4
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 2
+- training_steps: 50
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 99.4744       | 0.0003 | 1    | 3.5344          |
+| 106.9513      | 0.0067 | 25   | 2.6999          |
+| 99.1348       | 0.0133 | 50   | 2.6576          |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.5.0+cu124
+- Datasets 3.0.1
+- Tokenizers 0.20.1

adapter_model.bin

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