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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+WizardCoder-1B-V1.0-dpo-beta-0.01 - AWQ
+- Model creator: https://huggingface.co/AlekseyKorshuk/
+- Original model: https://huggingface.co/AlekseyKorshuk/WizardCoder-1B-V1.0-dpo-beta-0.01/
+
+
+
+
+Original model description:
+---
+license: bigcode-openrail-m
+base_model: WizardLM/WizardCoder-1B-V1.0
+tags:
+- axolotl
+- dpo
+- trl
+- dpo
+- generated_from_trainer
+model-index:
+- name: WizardCoder-1B-V1.0-dpo-beta-0.01
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.0`
+```yaml
+base_model: WizardLM/WizardCoder-1B-V1.0
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+trust_remote_code: true
+
+hub_model_id: AlekseyKorshuk/WizardCoder-1B-V1.0-dpo-beta-0.01
+hub_strategy: every_save
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+rl: dpo
+datasets:
+  - path: AlekseyKorshuk/evol-codealpaca-v1-dpo
+    split: train
+    type: wizardcoder.intel
+
+
+dataset_prepared_path:
+#val_set_size: 0.001
+output_dir: ./output
+
+sequence_len: 2048
+#sample_packing: false  # currently unsupported
+pad_to_sequence_len:
+
+lora_r:
+lora_alpha:
+lora_dropout:
+lora_target_modules:
+lora_target_linear:
+lora_fan_in_fan_out:
+
+wandb_project: ui-thesis
+wandb_entity:
+wandb_watch:
+wandb_name: ultrachat-stable-code-3b-dpo-chatml-beta-0.01
+wandb_log_model:
+
+gradient_accumulation_steps: 8
+micro_batch_size: 4
+num_epochs: 1
+optimizer: paged_adamw_8bit
+adam_beta1: 0.9
+adam_beta2: 0.95
+max_grad_norm: 1.0
+adam_epsilon: 0.00001
+lr_scheduler: cosine
+cosine_min_lr_ratio: 0.1
+learning_rate: 8.0e-7
+warmup_steps: 32
+#warmup_ratio: 0.1
+weight_decay: 0.01
+dpo_beta: 0.01
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+tf32: true
+#float16: true
+
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: false
+
+
+#evals_per_epoch: 5
+#eval_table_size: 8 # Approximate number of predictions sent to wandb depending on batch size. Enabled above 0. Default is 0
+#eval_table_max_new_tokens: 768 # Total number of tokens generated for predictions sent to wandb. Default is 128
+
+#chat_template: chatml
+#saves_per_epoch: 1
+save_steps: 500
+save_total_limit: 1
+seed: 42
+debug:
+deepspeed:
+
+
+fsdp:
+fsdp_config:
+resize_token_embeddings_to_32x: true
+
+```
+
+</details><br>
+
+# WizardCoder-1B-V1.0-dpo-beta-0.01
+
+This model is a fine-tuned version of [WizardLM/WizardCoder-1B-V1.0](https://huggingface.co/WizardLM/WizardCoder-1B-V1.0) on the None dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 8e-07
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 128
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 32
+- training_steps: 312
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0
+
+