End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: echarlaix/tiny-random-PhiForCausalLM
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: 6a18706f-1f89-4af9-a79b-aa75bcf38fa7
+  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: echarlaix/tiny-random-PhiForCausalLM
+bf16: auto
+chat_template: llama3
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - 7462b07f6259b24d_train_data.json
+  ds_type: json
+  format: custom
+  path: /workspace/input_data/7462b07f6259b24d_train_data.json
+  type:
+    field_instruction: startphrase
+    field_output: gold-ending
+    format: '{instruction}'
+    no_input_format: '{instruction}'
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+deepspeed: null
+do_eval: true
+early_stopping_patience: 3
+eval_batch_size: 4
+eval_max_new_tokens: 128
+eval_steps: 500
+evals_per_epoch: null
+flash_attention: true
+fp16: false
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 8
+gradient_checkpointing: true
+group_by_length: true
+hub_model_id: lesso14/6a18706f-1f89-4af9-a79b-aa75bcf38fa7
+hub_repo: null
+hub_strategy: checkpoint
+hub_token: null
+learning_rate: 0.000214
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: 50
+lora_alpha: 128
+lora_dropout: 0.15
+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_steps: 50000
+micro_batch_size: 4
+mlflow_experiment_name: /tmp/7462b07f6259b24d_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 10
+optimizer: adamw_torch_fused
+output_dir: miner_id_24
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+s2_attention: null
+sample_packing: false
+save_steps: 500
+saves_per_epoch: null
+seed: 140
+sequence_len: 1024
+special_tokens:
+  pad_token: <|endoftext|>
+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: 9611c628-3f80-4127-8fd5-47e5a88912ed
+wandb_project: 14a
+wandb_run: your_name
+wandb_runid: 9611c628-3f80-4127-8fd5-47e5a88912ed
+warmup_steps: 100
+weight_decay: 0.0
+xformers_attention: null
+
+```
+
+</details><br>
+
+# 6a18706f-1f89-4af9-a79b-aa75bcf38fa7
+
+This model is a fine-tuned version of [echarlaix/tiny-random-PhiForCausalLM](https://huggingface.co/echarlaix/tiny-random-PhiForCausalLM) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 6.7381
+
+## 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: 0.000214
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 140
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
+- training_steps: 27536
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss |
+|:-------------:|:------:|:-----:|:---------------:|
+| No log        | 0.0004 | 1     | 6.9353          |
+| 6.8024        | 0.1816 | 500   | 6.7948          |
+| 6.7909        | 0.3632 | 1000  | 6.7805          |
+| 6.7839        | 0.5447 | 1500  | 6.7707          |
+| 6.7782        | 0.7263 | 2000  | 6.7665          |
+| 6.7752        | 0.9079 | 2500  | 6.7620          |
+| 6.7731        | 1.0896 | 3000  | 6.7585          |
+| 6.7665        | 1.2712 | 3500  | 6.7563          |
+| 6.7647        | 1.4528 | 4000  | 6.7555          |
+| 6.7693        | 1.6343 | 4500  | 6.7542          |
+| 6.7655        | 1.8159 | 5000  | 6.7526          |
+| 6.7691        | 1.9975 | 5500  | 6.7526          |
+| 6.7587        | 2.1792 | 6000  | 6.7495          |
+| 6.7598        | 2.3608 | 6500  | 6.7491          |
+| 6.7643        | 2.5424 | 7000  | 6.7475          |
+| 6.7603        | 2.7240 | 7500  | 6.7470          |
+| 6.7626        | 2.9055 | 8000  | 6.7467          |
+| 6.7655        | 3.0872 | 8500  | 6.7455          |
+| 6.7542        | 3.2688 | 9000  | 6.7447          |
+| 6.7588        | 3.4504 | 9500  | 6.7444          |
+| 6.7615        | 3.6320 | 10000 | 6.7439          |
+| 6.7594        | 3.8136 | 10500 | 6.7434          |
+| 6.7554        | 3.9951 | 11000 | 6.7427          |
+| 6.7579        | 4.1769 | 11500 | 6.7426          |
+| 6.7579        | 4.3584 | 12000 | 6.7423          |
+| 6.7618        | 4.5400 | 12500 | 6.7421          |
+| 6.7577        | 4.7216 | 13000 | 6.7415          |
+| 6.758         | 4.9032 | 13500 | 6.7417          |
+| 6.7564        | 5.0849 | 14000 | 6.7413          |
+| 6.7575        | 5.2665 | 14500 | 6.7409          |
+| 6.7554        | 5.4480 | 15000 | 6.7403          |
+| 6.7527        | 5.6296 | 15500 | 6.7403          |
+| 6.7581        | 5.8112 | 16000 | 6.7402          |
+| 6.7663        | 5.9928 | 16500 | 6.7398          |
+| 6.765         | 6.1745 | 17000 | 6.7397          |
+| 6.7492        | 6.3561 | 17500 | 6.7396          |
+| 6.7621        | 6.5377 | 18000 | 6.7392          |
+| 6.7587        | 6.7192 | 18500 | 6.7391          |
+| 6.7595        | 6.9008 | 19000 | 6.7388          |
+| 6.7544        | 7.0825 | 19500 | 6.7388          |
+| 6.76          | 7.2641 | 20000 | 6.7387          |
+| 6.7539        | 7.4457 | 20500 | 6.7386          |
+| 6.7574        | 7.6273 | 21000 | 6.7385          |
+| 6.7517        | 7.8088 | 21500 | 6.7384          |
+| 6.7531        | 7.9904 | 22000 | 6.7383          |
+| 6.756         | 8.1721 | 22500 | 6.7381          |
+| 6.754         | 8.3537 | 23000 | 6.7381          |
+| 6.7558        | 8.5353 | 23500 | 6.7381          |
+| 6.7533        | 8.7169 | 24000 | 6.7380          |
+| 6.7583        | 8.8985 | 24500 | 6.7384          |
+| 6.7586        | 9.0802 | 25000 | 6.7384          |
+| 6.7559        | 9.2617 | 25500 | 6.7381          |
+
+
+### 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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