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--- |
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license: mit |
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base_model: microsoft/Phi-3-medium-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: outputs/phi3-medium-128k-14b.8e6 |
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results: [] |
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--- |
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**Exllamav2** quant (**exl2** / **4.25 bpw**) made with ExLlamaV2 v0.0.21 |
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Other EXL2 quants: |
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| **Quant** | **Model Size** | **lm_head** | |
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| ----- | ---------- | ------- | |
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|<center>**[2.2](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-2_2bpw_exl2)**</center> | <center>4032 MB</center> | <center>6</center> | |
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|<center>**[2.5](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-2_5bpw_exl2)**</center> | <center>4500 MB</center> | <center>6</center> | |
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|<center>**[3.0](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-3_0bpw_exl2)**</center> | <center>5312 MB</center> | <center>6</center> | |
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|<center>**[3.5](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-3_5bpw_exl2)**</center> | <center>6124 MB</center> | <center>6</center> | |
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|<center>**[3.75](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-3_75bpw_exl2)**</center> | <center>6531 MB</center> | <center>6</center> | |
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|<center>**[4.0](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-4_0bpw_exl2)**</center> | <center>6937 MB</center> | <center>6</center> | |
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|<center>**[4.25](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-4_25bpw_exl2)**</center> | <center>7340 MB</center> | <center>6</center> | |
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|<center>**[5.0](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-5_0bpw_exl2)**</center> | <center>8554 MB</center> | <center>6</center> | |
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|<center>**[6.0](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-6_0bpw_exl2)**</center> | <center>10210 MB</center> | <center>8</center> | |
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|<center>**[6.5](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-6_5bpw_exl2)**</center> | <center>11018 MB</center> | <center>8</center> | |
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|<center>**[8.0](https://huggingface.co/Zoyd/shisa-ai_shisa-v1-phi3-14b-8_0bpw_exl2)**</center> | <center>12332 MB</center> | <center>8</center> | |
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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-medium-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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use_wandb: true |
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wandb_project: shisa-v2 |
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wandb_entity: augmxnt |
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wandb_name: shisa-llama3-70b-v1.8e6 |
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chat_template: chatml |
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datasets: |
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- path: augmxnt/ultra-orca-boros-en-ja-v1 |
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type: sharegpt |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.05 |
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output_dir: ./outputs/phi3-medium-128k-14b.8e6 |
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sequence_len: 4096 |
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sample_packing: true |
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pad_to_sequence_len: true |
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neftune_noise_alpha: 5 |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 3 |
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optimizer: paged_adamw_8bit |
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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: linear |
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learning_rate: 0.000008 |
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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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evals_per_epoch: 4 |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: axolotl/deepspeed_configs/zero3_bf16.json |
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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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# outputs/phi3-medium-128k-14b.8e6 |
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This model is a fine-tuned version of [microsoft/Phi-3-medium-128k-instruct](https://huggingface.co/microsoft/Phi-3-medium-128k-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3339 |
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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: 8e-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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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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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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| 2.8309 | 0.0021 | 1 | 2.3406 | |
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| 0.7688 | 0.2513 | 121 | 0.4958 | |
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| 0.6435 | 0.5026 | 242 | 0.3830 | |
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| 0.5286 | 0.7539 | 363 | 0.3626 | |
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| 0.5559 | 1.0052 | 484 | 0.3549 | |
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| 0.4651 | 1.2425 | 605 | 0.3486 | |
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| 0.5294 | 1.4938 | 726 | 0.3432 | |
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| 0.5453 | 1.7451 | 847 | 0.3392 | |
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| 0.5258 | 1.9964 | 968 | 0.3376 | |
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| 0.4805 | 2.2331 | 1089 | 0.3357 | |
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| 0.4552 | 2.4844 | 1210 | 0.3352 | |
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| 0.5358 | 2.7357 | 1331 | 0.3339 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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