End of training

README.md

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+---
+library_name: peft
+base_model: TitanML/tiny-mixtral
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: b279808d-b2c3-4b2c-a69a-9d224adb42fe
+  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: TitanML/tiny-mixtral
+bf16: true
+chat_template: llama3
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - 1626557c75bc8215_train_data.json
+  ds_type: json
+  format: custom
+  path: /workspace/input_data/1626557c75bc8215_train_data.json
+  type:
+    field_instruction: instruction
+    field_output: output
+    format: '{instruction}'
+    no_input_format: '{instruction}'
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+deepspeed: null
+device_map: auto
+do_eval: true
+early_stopping_patience: 2
+eval_batch_size: 4
+eval_max_new_tokens: 128
+eval_steps: 150
+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: true
+hub_model_id: nttx/b279808d-b2c3-4b2c-a69a-9d224adb42fe
+hub_repo: null
+hub_strategy: checkpoint
+hub_token: null
+learning_rate: 0.0002
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: 50
+lora_alpha: 128
+lora_dropout: 0.3
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 64
+lora_target_linear: true
+lr_scheduler: cosine
+max_grad_norm: 1.0
+max_memory:
+  0: 75GB
+max_steps: 3000
+micro_batch_size: 4
+mlflow_experiment_name: /tmp/1626557c75bc8215_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 10
+optim_args:
+  adam_beta1: 0.9
+  adam_beta2: 0.95
+  adam_epsilon: 1e-5
+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: 150
+saves_per_epoch: null
+sequence_len: 512
+special_tokens:
+  pad_token: </s>
+strict: false
+tf32: true
+tokenizer_type: AutoTokenizer
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0.05
+wandb_entity: null
+wandb_mode: online
+wandb_name: 7950e38d-4ae2-4e1f-a6a0-0107e2b31c7d
+wandb_project: Gradients-On-Demand
+wandb_run: your_name
+wandb_runid: 7950e38d-4ae2-4e1f-a6a0-0107e2b31c7d
+warmup_steps: 50
+weight_decay: 0.0
+xformers_attention: null
+
+```
+
+</details><br>
+
+# b279808d-b2c3-4b2c-a69a-9d224adb42fe
+
+This model is a fine-tuned version of [TitanML/tiny-mixtral](https://huggingface.co/TitanML/tiny-mixtral) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 4.8374
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_BNB 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: 50
+- training_steps: 3000
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| No log        | 0.0003 | 1    | 10.5753         |
+| 8.3438        | 0.0492 | 150  | 8.0755          |
+| 6.9827        | 0.0983 | 300  | 6.9109          |
+| 6.5081        | 0.1475 | 450  | 6.4205          |
+| 6.207         | 0.1966 | 600  | 6.1038          |
+| 5.9758        | 0.2458 | 750  | 5.9017          |
+| 5.7978        | 0.2950 | 900  | 5.7243          |
+| 5.5757        | 0.3441 | 1050 | 5.5193          |
+| 5.5036        | 0.3933 | 1200 | 5.3982          |
+| 5.3336        | 0.4424 | 1350 | 5.2550          |
+| 5.2624        | 0.4916 | 1500 | 5.1578          |
+| 5.1754        | 0.5408 | 1650 | 5.0719          |
+| 5.1936        | 0.5899 | 1800 | 5.0090          |
+| 5.0071        | 0.6391 | 1950 | 4.9581          |
+| 5.0504        | 0.6882 | 2100 | 4.9146          |
+| 4.9615        | 0.7374 | 2250 | 4.8807          |
+| 4.9688        | 0.7866 | 2400 | 4.8611          |
+| 4.9255        | 0.8357 | 2550 | 4.8456          |
+| 5.0045        | 0.8849 | 2700 | 4.8406          |
+| 4.9882        | 0.9340 | 2850 | 4.8395          |
+| 4.9035        | 0.9832 | 3000 | 4.8374          |
+
+
+### 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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