Update README.md

README.md

@@ -14,146 +14,20 @@ model-index:
 should probably proofread and complete it, then remove this comment. -->
 
 [<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)
-<details><summary>See axolotl config</summary>
 
-axolotl version: `0.4.1`
-```yaml
-# python -m axolotl.cli.preprocess adventure-l31.yml
-# accelerate launch -m axolotl.cli.train adventure-l31.yml
-# python -m axolotl.cli.merge_lora adventure-l31.yml
+# Meta-Llama-3.1-8B-Adventure-QLoRA
 
-base_model: unsloth/Meta-Llama-3.1-8B
-model_type: AutoModelForCausalLM
-tokenizer_type: AutoTokenizer
-
-load_in_8bit: false
-load_in_4bit: true
-strict: false
-sequence_len: 8192 # 99% vram
-bf16: auto
-fp16:
-tf32: false
-flash_attention: true
-special_tokens:
-
-# Data
-dataset_prepared_path: last_run_prepared
-datasets:
-  - path: ColumbidAI/adventure-8k
-    type: completion
-warmup_steps: 20
-shuffle_merged_datasets: true
-
-save_safetensors: true
-saves_per_epoch: 4
-save_total_limit: 2
-
-# WandB
-wandb_project: L31-A
-wandb_entity:
-
-# Iterations
-num_epochs: 1
-
-# Output
-output_dir: ./adventure-command-r-workspace
-hub_model_id: ToastyPigeon/adventure-nemo-ws
-hub_strategy: "all_checkpoints"
-
-# Sampling
-sample_packing: true
-pad_to_sequence_len: true
-
-# Batching
-gradient_accumulation_steps: 2
-micro_batch_size: 8
-gradient_checkpointing: 'unsloth'
-gradient_checkpointing_kwargs:
-   use_reentrant: true
-
-#unsloth_cross_entropy_loss: true
-#unsloth_lora_mlp: true
-#unsloth_lora_qkv: true
-#unsloth_lora_o: true
-
-# Evaluation
-val_set_size: 0.01
-evals_per_epoch: 5
-eval_table_size:
-eval_max_new_tokens: 256
-eval_sample_packing: false
-eval_batch_size: 1
-
-# LoRA
-adapter: qlora
-lora_model_dir:
-lora_r: 64
-lora_alpha: 32
-lora_dropout: 0.125
-lora_target_linear: 
-lora_fan_in_fan_out:
-lora_target_modules:
-  - gate_proj
-  - down_proj
-  - up_proj
-  - q_proj
-  - v_proj
-  - k_proj
-  - o_proj
-lora_modules_to_save:
+This LoRA is trained on Llama 3.1 8B **base** using completion format. 
 
-# Optimizer
-optimizer: paged_adamw_8bit # adamw_8bit
-lr_scheduler: cosine
-learning_rate: 0.00005
-lr_scheduler: cosine_with_min_lr
-lr_scheduler_kwargs:
-    min_lr: 0.000005
-weight_decay: 0.01
-max_grad_norm: 20.0
+The datasets used were: 
+- Spring Dragon
+- Skein
 
-# Misc
-train_on_inputs: false
-group_by_length: false
-early_stopping_patience:
-local_rank:
-logging_steps: 1
-xformers_attention:
-debug:
-#deepspeed: /workspace/axolotl/deepspeed_configs/zero3.json # previously blank
-fsdp:
-fsdp_config:
+This is not an instruct model and **no instruct format was used.** 
 
+The intended use is with text completion where user input is given with `> User Input`. This is the default for Kobold Lite Adventure mode. 
 
-plugins:
-  - axolotl.integrations.liger.LigerPlugin
-liger_rope: true
-liger_rms_norm: true
-liger_swiglu: true
-liger_fused_linear_cross_entropy: true
-```
-
-</details><br>
-
-# adventure-nemo-ws
-
-This model is a fine-tuned version of [unsloth/Meta-Llama-3.1-8B](https://huggingface.co/unsloth/Meta-Llama-3.1-8B) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 2.3893
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
+If merged into an instruct model, it should impart the flavor of the text adventure data. Use whatever the instruct model's format is for instruct.
 
 ### Training hyperparameters
 
@@ -169,16 +43,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_steps: 20
 - num_epochs: 1
 
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 2.2246        | 0.0045 | 1    | 2.4988          |
-| 2.1034        | 0.2013 | 45   | 2.4257          |
-| 2.2138        | 0.4027 | 90   | 2.4077          |
-| 2.1541        | 0.6040 | 135  | 2.3941          |
-| 2.0555        | 0.8054 | 180  | 2.3893          |
-
 
 ### Framework versions