End of training

README.md

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+---
+library_name: peft
+license: llama3.1
+base_model: unsloth/Meta-Llama-3.1-8B
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: 8884a407-fa97-46e8-9237-d87a95df04d1
+  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: unsloth/Meta-Llama-3.1-8B
+bf16: auto
+bnb_config_kwargs:
+  bnb_4bit_quant_type: nf4
+  bnb_4bit_use_double_quant: true
+chat_template: llama3
+cosine_min_lr_ratio: 0.1
+data_processes: 16
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - MATH-Hard_train_data.json
+  ds_type: json
+  path: /workspace/input_data/MATH-Hard_train_data.json
+  type:
+    field_input: problem
+    field_instruction: type
+    field_output: solution
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+deepspeed: null
+device_map: '{'''':torch.cuda.current_device()}'
+do_eval: true
+early_stopping_patience: 1
+eval_batch_size: 1
+eval_sample_packing: false
+eval_steps: 25
+evaluation_strategy: steps
+flash_attention: true
+fp16: null
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 32
+gradient_checkpointing: true
+group_by_length: true
+hub_model_id: cwaud/8884a407-fa97-46e8-9237-d87a95df04d1
+hub_repo: cwaud
+hub_strategy: checkpoint
+hub_token: null
+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: 750
+micro_batch_size: 1
+mlflow_experiment_name: /tmp/MATH-Hard_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 4
+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
+resume_from_checkpoint: null
+s2_attention: null
+sample_packing: false
+save_steps: 50
+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: rayonlabs-rayon-labs
+wandb_mode: online
+wandb_project: Public_TuningSN
+wandb_run: miner_id_24
+wandb_runid: 8884a407-fa97-46e8-9237-d87a95df04d1
+warmup_raio: 0.03
+warmup_ratio: 0.05
+weight_decay: 0.01
+xformers_attention: null
+
+```
+
+</details><br>
+
+# 8884a407-fa97-46e8-9237-d87a95df04d1
+
+This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7643
+
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 5
+- training_steps: 109
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.666         | 0.0368 | 1    | 0.9461          |
+| 0.7893        | 0.9195 | 25   | 0.7771          |
+| 0.5965        | 1.8391 | 50   | 0.7638          |
+| 0.5897        | 2.7586 | 75   | 0.7600          |
+| 0.6974        | 3.6782 | 100  | 0.7643          |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.45.2
+- Pytorch 2.4.1+cu124
+- Datasets 3.0.1
+- Tokenizers 0.20.1

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