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--- |
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license: mit |
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base_model: microsoft/Phi-3-mini-128k-instruct |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: phi3-sft-out |
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.0` |
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```yaml |
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base_model: microsoft/Phi-3-mini-128k-instruct |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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trust_remote_code: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: sosoai/mixed_dataset |
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type: alpaca |
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dataset_prepared_path: |
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val_set_size: 0.05 |
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output_dir: ./phi3-sft-out |
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sequence_len: 2048 |
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sample_packing: true |
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pad_to_sequence_len: true |
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adapter: |
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lora_model_dir: |
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lora_r: |
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lora_alpha: |
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lora_dropout: |
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lora_target_linear: |
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lora_fan_in_fan_out: |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 1 |
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micro_batch_size: 2 |
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num_epochs: 5 |
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optimizer: adamw_torch |
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adam_beta2: 0.95 |
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adam_epsilon: 0.00001 |
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max_grad_norm: 1.0 |
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lr_scheduler: cosine |
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learning_rate: 0.000003 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: true |
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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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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 100 |
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eval_sample_packing: False |
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evals_per_epoch: 4 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: |
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weight_decay: 0.1 |
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fsdp: |
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fsdp_config: |
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resize_token_embeddings_to_32x: true |
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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-sft-out |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2406 |
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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: 3e-06 |
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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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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 4.6772 | 0.0 | 1 | 1.3794 | |
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| 3.1471 | 0.25 | 175 | 1.2942 | |
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| 3.0306 | 0.5 | 350 | 1.2572 | |
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| 2.7486 | 0.75 | 525 | 1.2491 | |
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| 2.7702 | 1.0 | 700 | 1.2467 | |
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| 2.6302 | 1.24 | 875 | 1.2458 | |
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| 2.8356 | 1.49 | 1050 | 1.2436 | |
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| 2.7697 | 1.74 | 1225 | 1.2418 | |
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| 2.7226 | 2.0 | 1400 | 1.2415 | |
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| 2.7363 | 2.23 | 1575 | 1.2411 | |
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| 2.6754 | 2.48 | 1750 | 1.2407 | |
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| 2.9697 | 2.73 | 1925 | 1.2407 | |
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| 2.6213 | 2.99 | 2100 | 1.2406 | |
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| 2.6752 | 3.23 | 2275 | 1.2407 | |
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| 2.7226 | 3.48 | 2450 | 1.2404 | |
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| 2.6131 | 3.73 | 2625 | 1.2405 | |
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| 2.7255 | 3.98 | 2800 | 1.2404 | |
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| 2.7335 | 4.21 | 2975 | 1.2404 | |
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| 2.7924 | 4.46 | 3150 | 1.2406 | |
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| 2.6851 | 4.71 | 3325 | 1.2406 | |
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### Framework versions |
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- Transformers 4.40.0.dev0 |
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- Pytorch 2.1.1 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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