End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: unsloth/Qwen2.5-1.5B-Instruct
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: 84afe1d4-4257-4eb1-972d-6df752fb4b25
+  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: qlora
+auto_resume_from_checkpoints: true
+base_model: unsloth/Qwen2.5-1.5B-Instruct
+bf16: auto
+chat_template: llama3
+dataset_prepared_path: null
+dataset_processes: 6
+datasets:
+- data_files:
+  - f498211ddfc39ad0_train_data.json
+  ds_type: json
+  format: custom
+  path: /workspace/input_data/f498211ddfc39ad0_train_data.json
+  type:
+    field_instruction: text
+    field_output: text_description
+    format: '{instruction}'
+    no_input_format: '{instruction}'
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+deepspeed: null
+early_stopping_patience: 3
+eval_max_new_tokens: 128
+eval_steps: 200
+eval_table_size: null
+evals_per_epoch: null
+flash_attention: true
+fp16: false
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 4
+gradient_checkpointing: true
+group_by_length: false
+hub_model_id: error577/84afe1d4-4257-4eb1-972d-6df752fb4b25
+hub_repo: null
+hub_strategy: checkpoint
+hub_token: null
+learning_rate: 0.0002
+load_in_4bit: true
+load_in_8bit: false
+local_rank: null
+logging_steps: 1
+lora_alpha: 64
+lora_dropout: 0.1
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 32
+lora_target_linear: true
+lr_scheduler: cosine
+max_grad_norm: 1.0
+max_steps: null
+micro_batch_size: 2
+mlflow_experiment_name: /tmp/f498211ddfc39ad0_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 3
+optimizer: adamw_bnb_8bit
+output_dir: miner_id_24
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+s2_attention: null
+sample_packing: false
+save_steps: 200
+sequence_len: 512
+strict: false
+tf32: false
+tokenizer_type: AutoTokenizer
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0.005
+wandb_entity: null
+wandb_mode: online
+wandb_name: c45098d1-819e-4d15-988b-1e7aa32b705d
+wandb_project: Gradients-On-Demand
+wandb_run: your_name
+wandb_runid: c45098d1-819e-4d15-988b-1e7aa32b705d
+warmup_steps: 30
+weight_decay: 0.0
+xformers_attention: null
+
+```
+
+</details><br>
+
+# 84afe1d4-4257-4eb1-972d-6df752fb4b25
+
+This model is a fine-tuned version of [unsloth/Qwen2.5-1.5B-Instruct](https://huggingface.co/unsloth/Qwen2.5-1.5B-Instruct) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5277
+
+## 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: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 30
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 4.2872        | 0.0001 | 1    | 4.2889          |
+| 0.8655        | 0.0105 | 200  | 0.6744          |
+| 0.6984        | 0.0209 | 400  | 0.6216          |
+| 0.6142        | 0.0314 | 600  | 0.6047          |
+| 0.5007        | 0.0419 | 800  | 0.5945          |
+| 0.7687        | 0.0523 | 1000 | 0.6034          |
+| 0.7365        | 0.0628 | 1200 | 0.5816          |
+| 0.6433        | 0.0732 | 1400 | 0.5778          |
+| 0.7683        | 0.0837 | 1600 | 0.5629          |
+| 0.5652        | 0.0942 | 1800 | 0.5651          |
+| 0.643         | 0.1046 | 2000 | 0.5693          |
+| 0.5288        | 0.1151 | 2200 | 0.5616          |
+| 0.7206        | 0.1256 | 2400 | 0.5566          |
+| 0.4707        | 0.1360 | 2600 | 0.5513          |
+| 0.5978        | 0.1465 | 2800 | 0.5490          |
+| 0.4808        | 0.1569 | 3000 | 0.5403          |
+| 0.4192        | 0.1674 | 3200 | 0.5361          |
+| 0.5707        | 0.1779 | 3400 | 0.5439          |
+| 0.5219        | 0.1883 | 3600 | 0.5353          |
+| 0.5931        | 0.1988 | 3800 | 0.5475          |
+| 0.3744        | 0.2093 | 4000 | 0.5371          |
+| 0.5987        | 0.2197 | 4200 | 0.5279          |
+| 0.4643        | 0.2302 | 4400 | 0.5257          |
+| 0.4355        | 0.2406 | 4600 | 0.5312          |
+| 0.6844        | 0.2511 | 4800 | 0.5318          |
+| 0.4962        | 0.2616 | 5000 | 0.5277          |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.5.0+cu124
+- Datasets 3.0.1
+- Tokenizers 0.20.1

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