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--- |
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library_name: transformers |
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base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: outputs/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/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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base_model: Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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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: PocketDoc/Dans-MemoryCore-CoreCurriculum-Small |
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type: sharegpt |
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conversation: chatml |
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- path: NewEden/Kalo-Opus-Instruct-22k-Refusal-Murdered |
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type: sharegpt |
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conversation: chatml |
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- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned |
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type: sharegpt |
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conversation: chatml |
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- path: NewEden/Gryphe-Sonnet-3.5-35k-Subset |
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type: sharegpt |
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conversation: chatml |
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- path: Nitral-AI/Reasoning-1shot_ShareGPT |
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type: sharegpt |
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conversation: chatml |
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- path: Nitral-AI/GU_Instruct-ShareGPT |
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type: sharegpt |
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conversation: chatml |
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- path: Nitral-AI/Medical_Instruct-ShareGPT |
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type: sharegpt |
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conversation: chatml |
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- path: AquaV/Resistance-Sharegpt |
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type: sharegpt |
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conversation: chatml |
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- path: AquaV/US-Army-Survival-Sharegpt |
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type: sharegpt |
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conversation: chatml |
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- path: Gryphe/Sonnet3.5-SlimOrcaDedupCleaned |
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type: sharegpt |
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conversation: chatml |
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chat_template: chatml |
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val_set_size: 0.002 |
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output_dir: ./outputs/out |
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adapter: |
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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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sequence_len: 8192 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_swiglu: true |
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liger_fused_linear_cross_entropy: true |
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wandb_project: mini8B |
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wandb_entity: |
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wandb_watch: |
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wandb_name: mini8B |
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wandb_log_model: |
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gradient_accumulation_steps: 4 |
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micro_batch_size: 2 |
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num_epochs: 2 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.00001 |
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weight_decay: 0.05 |
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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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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_ratio: 0.1 |
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evals_per_epoch: 4 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 2 |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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pad_token: <pad> |
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``` |
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</details><br> |
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# outputs/out |
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This model is a fine-tuned version of [Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML](https://huggingface.co/Dans-DiscountModels/Mistral-NeMo-Minitron-8B-Base-ChatML) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5341 |
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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: 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=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 91 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.2548 | 0.0022 | 1 | 2.0884 | |
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| 0.7712 | 0.2503 | 114 | 1.6165 | |
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| 0.7566 | 0.5005 | 228 | 1.5734 | |
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| 0.7241 | 0.7508 | 342 | 1.5579 | |
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| 0.6994 | 1.0011 | 456 | 1.5401 | |
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| 0.6186 | 1.2499 | 570 | 1.5433 | |
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| 0.6102 | 1.5003 | 684 | 1.5366 | |
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| 0.5926 | 1.7507 | 798 | 1.5341 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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