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--- |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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library_name: peft |
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license: mit |
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tags: |
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- axolotl |
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- generated_from_trainer |
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model-index: |
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- name: phi3-nosys-gpt4ominiplans-27k-512rank-long |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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# model and tokenizer |
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base_model: microsoft/Phi-3-mini-4k-instruct # change for model |
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trust_remote_code: true |
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sequence_len: 2048 |
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strict: false |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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bf16: auto |
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pad_to_sequence_len: true |
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save_safetensors: true |
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datasets: |
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- path: verifiers-for-code/sampled_10k_from_27k |
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type: completion |
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field: text_nosys_phi |
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train_on_split: train |
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val_set_size: 0.05 |
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# lora |
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adapter: lora |
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lora_r: 512 |
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lora_alpha: 32 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_modules_to_save: |
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- embed_tokens |
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- lm_head |
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use_rslora: true |
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# logging |
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wandb_project: valeris |
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wandb_name: phi3-nosys-gpt4ominiplans-27k-512rank-long |
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output_dir: ./outputs/phi3-nosys-gpt4ominiplans-27k-512rank-long |
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gradient_accumulation_steps: 2 |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: true |
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micro_batch_size: 2 |
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num_epochs: 3 |
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eval_batch_size: 2 |
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warmup_ratio: 0.05 |
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learning_rate: 1e-5 |
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lr_scheduler: cosine |
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optimizer: adamw_torch |
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hub_model_id: verifiers-for-code/phi3-nosys-gpt4ominiplans-27k-512rank-long |
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push_to_hub: true |
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hub_strategy: all_checkpoints |
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hub_always_push: true |
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evals_per_epoch: 8 |
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saves_per_epoch: 4 |
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logging_steps: 1 |
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# eval_table_size: 10 |
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# eval_max_new_tokens: 512 |
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tokens: ["<thinking>", "</thinking>", "<plan>", "</plan>"] |
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special_tokens: |
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pad_token: "<|endoftext|>" |
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``` |
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</details><br> |
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# phi3-nosys-gpt4ominiplans-27k-512rank-long |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6378 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 44 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.0833 | 0.0034 | 1 | 1.0330 | |
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| 1.0093 | 0.1279 | 38 | 0.9910 | |
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| 0.9169 | 0.2559 | 76 | 0.8668 | |
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| 0.795 | 0.3838 | 114 | 0.7676 | |
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| 0.6999 | 0.5118 | 152 | 0.7243 | |
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| 0.7246 | 0.6397 | 190 | 0.6989 | |
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| 0.6873 | 0.7677 | 228 | 0.6816 | |
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| 0.7014 | 0.8956 | 266 | 0.6687 | |
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| 0.6586 | 1.0236 | 304 | 0.6585 | |
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| 0.6532 | 1.1515 | 342 | 0.6511 | |
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| 0.6334 | 1.2795 | 380 | 0.6463 | |
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| 0.5968 | 1.4074 | 418 | 0.6434 | |
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| 0.6366 | 1.5354 | 456 | 0.6414 | |
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| 0.6126 | 1.6633 | 494 | 0.6400 | |
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| 0.6564 | 1.7912 | 532 | 0.6391 | |
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| 0.6296 | 1.9192 | 570 | 0.6387 | |
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| 0.6225 | 2.0471 | 608 | 0.6383 | |
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| 0.6354 | 2.1751 | 646 | 0.6381 | |
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| 0.6111 | 2.3030 | 684 | 0.6379 | |
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| 0.5899 | 2.4310 | 722 | 0.6378 | |
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| 0.6415 | 2.5589 | 760 | 0.6378 | |
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| 0.6443 | 2.6869 | 798 | 0.6377 | |
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| 0.6103 | 2.8148 | 836 | 0.6377 | |
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| 0.6451 | 2.9428 | 874 | 0.6378 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.44.0.dev0 |
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- Pytorch 2.4.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
