RichardErkhov
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README.md
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Quantization made by Richard Erkhov.
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[Github](https://github.com/RichardErkhov)
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[Discord](https://discord.gg/pvy7H8DZMG)
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[Request more models](https://github.com/RichardErkhov/quant_request)
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ultrachat-evolcode-phi-2-sft-chatml - bnb 8bits
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- Model creator: https://huggingface.co/AlekseyKorshuk/
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- Original model: https://huggingface.co/AlekseyKorshuk/ultrachat-evolcode-phi-2-sft-chatml/
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Original model description:
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---
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license: mit
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base_model: AlekseyKorshuk/ultrachat-phi-2-sft-chatml
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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: ultrachat-evolcode-phi-2-sft-chatml
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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: AlekseyKorshuk/ultrachat-phi-2-sft-chatml
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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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hub_model_id: AlekseyKorshuk/ultrachat-evolcode-phi-2-sft-chatml
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hub_strategy: every_save
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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: AlekseyKorshuk/evol-codealpaca-v1-sft
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type: sharegpt
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conversation: chatml
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dataset_prepared_path:
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val_set_size: 0
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output_dir: ./output
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sequence_len: 2048
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sample_packing: false
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pad_to_sequence_len:
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lora_r:
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lora_alpha:
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lora_dropout:
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lora_target_modules:
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lora_target_linear:
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lora_fan_in_fan_out:
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wandb_project: ui-thesis
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wandb_entity:
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wandb_watch:
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wandb_name: ultrachat-evolcode-phi-2-sft-chatml
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wandb_log_model:
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gradient_accumulation_steps: 2
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micro_batch_size: 16
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num_epochs: 1
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optimizer: paged_adamw_8bit
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adam_beta1: 0.9
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adam_beta2: 0.95
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max_grad_norm: 1.0
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adam_epsilon: 0.00001
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lr_scheduler: cosine
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cosine_min_lr_ratio: 0.1
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learning_rate: 2e-5
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warmup_ratio: 0.1
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weight_decay: 0.1
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train_on_inputs: false
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group_by_length: false
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bf16: true
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fp16: false
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tf32: true
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#bf16: false
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#fp16: false
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#tf32: false
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#float16: 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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evals_per_epoch: 0
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eval_table_size: 8 # Approximate number of predictions sent to wandb depending on batch size. Enabled above 0. Default is 0
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eval_table_max_new_tokens: 768 # Total number of tokens generated for predictions sent to wandb. Default is 128
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eval_sample_packing: false
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chat_template: chatml
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saves_per_epoch: 5
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save_total_limit: 1
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seed: 42
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debug:
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deepspeed:
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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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```
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</details><br>
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# ultrachat-evolcode-phi-2-sft-chatml
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This model is a fine-tuned version of [AlekseyKorshuk/ultrachat-phi-2-sft-chatml](https://huggingface.co/AlekseyKorshuk/ultrachat-phi-2-sft-chatml) on the None dataset.
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 128
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- total_eval_batch_size: 64
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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: 7
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- num_epochs: 1
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### Training results
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### Framework versions
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- Transformers 4.37.0
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- Pytorch 2.1.2+cu118
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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