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README.md
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---
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library_name: transformers
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base_model: NewEden/Hamanasu-KTO-4B
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tags:
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- axolotl
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- generated_from_trainer
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datasets:
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- PocketDoc/Dans-Prosemaxx-Cowriter-3-S
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- PocketDoc/Dans-Prosemaxx-Adventure
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- PocketDoc/Dans-Failuremaxx-Adventure-3
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- PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-2
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- PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-3
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- PocketDoc/Dans-Prosemaxx-InstructWriter-Continue-2
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- PocketDoc/Dans-Prosemaxx-Instructwriter-Long
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model-index:
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- name: Hamanasu-4B-Adventure-Final-Hopefully
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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: `0.8.0.dev0`
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```yaml
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base_model: NewEden/Hamanasu-KTO-4B
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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hub_model_id: NewEden/Hamanasu-4B-Adventure-Final-Hopefully
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hub_strategy: "all_checkpoints"
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push_dataset_to_hub:
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hf_use_auth_token: true
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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- axolotl.integrations.cut_cross_entropy.CutCrossEntropyPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_layer_norm: true
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liger_glu_activation: true
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liger_fused_linear_cross_entropy: false
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cut_cross_entropy: 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: PocketDoc/Dans-Prosemaxx-Cowriter-3-S
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type: dan-chat-advanced
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- path: PocketDoc/Dans-Prosemaxx-Adventure
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type: dan-chat-advanced
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- path: PocketDoc/Dans-Failuremaxx-Adventure-3
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type: dan-chat-advanced
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- path: PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-2
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type: dan-chat-advanced
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- path: PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-3
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type: dan-chat-advanced
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- path: PocketDoc/Dans-Prosemaxx-InstructWriter-Continue-2
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type: dan-chat-advanced
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- path: PocketDoc/Dans-Prosemaxx-Instructwriter-Long
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type: dan-chat-advanced
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shuffle_merged_datasets: true
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dataset_prepared_path: prepared_data
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val_set_size: 0.01
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output_dir: ./adventure
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sequence_len: 32768
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sample_packing: true
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pad_to_sequence_len: true
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eval_sample_packing: true
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wandb_project: tavbussy
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wandb_entity:
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wandb_watch:
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wandb_name: adventure-attempt-02
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wandb_log_model:
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gradient_accumulation_steps: 1
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micro_batch_size: 4
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num_epochs: 4
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optimizer: adamw_bnb_8bit
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lr_scheduler: cosine
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learning_rate: 5e-6
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max_grad_norm: 0.1
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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: false
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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_steps: 25
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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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weight_decay: 0.02
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fsdp:
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fsdp_config:
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special_tokens:
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pad_token: <|finetune_right_pad_id|>
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```
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</details><br>
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# Hamanasu-4B-Adventure-Final-Hopefully
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This model is a fine-tuned version of [NewEden/Hamanasu-KTO-4B](https://huggingface.co/NewEden/Hamanasu-KTO-4B) on the PocketDoc/Dans-Prosemaxx-Cowriter-3-S, the PocketDoc/Dans-Prosemaxx-Adventure, the PocketDoc/Dans-Failuremaxx-Adventure-3, the PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-2, the PocketDoc/Dans-Prosemaxx-InstructWriter-ZeroShot-3, the PocketDoc/Dans-Prosemaxx-InstructWriter-Continue-2 and the PocketDoc/Dans-Prosemaxx-Instructwriter-Long datasets.
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It achieves the following results on the evaluation set:
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- Loss: 2.4143
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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: 5e-06
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- train_batch_size: 4
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- eval_batch_size: 4
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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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- total_train_batch_size: 16
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- total_eval_batch_size: 16
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 25
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- num_epochs: 4.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 2.5668 | 0.0068 | 1 | 2.5806 |
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| 2.455 | 0.2534 | 37 | 2.4450 |
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| 2.4115 | 0.5068 | 74 | 2.4323 |
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| 2.3298 | 0.7603 | 111 | 2.4223 |
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| 2.322 | 1.0137 | 148 | 2.4178 |
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| 2.2661 | 1.2671 | 185 | 2.4178 |
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| 2.2482 | 1.5205 | 222 | 2.4155 |
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| 2.3707 | 1.7740 | 259 | 2.4115 |
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| 2.293 | 2.0274 | 296 | 2.4132 |
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| 2.3085 | 2.2808 | 333 | 2.4137 |
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| 2.1902 | 2.5342 | 370 | 2.4123 |
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| 2.216 | 2.7877 | 407 | 2.4112 |
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| 2.3081 | 3.0411 | 444 | 2.4123 |
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| 2.1989 | 3.2945 | 481 | 2.4142 |
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| 2.2527 | 3.5479 | 518 | 2.4142 |
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| 2.2419 | 3.8014 | 555 | 2.4143 |
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### Framework versions
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- Transformers 4.50.0
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- Pytorch 2.5.1+cu124
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- Datasets 3.4.1
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- Tokenizers 0.21.1
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