ToastyPigeon
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mistral-small-adventure-qlora

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 ---
 base_model: mistralai/Mistral-Small-Instruct-2409
 library_name: peft
 ---
-# Model Card for Model ID
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-## Model Details
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 ### Framework versions
-- PEFT 0.13.0

 ---
 base_model: mistralai/Mistral-Small-Instruct-2409
 library_name: peft
+license: other
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: mistral-small-adventure-qlora
+  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/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
+# huggingface-cli login --token $hf_key && wandb login $wandb_key
+# python -m axolotl.cli.preprocess ms-adventure.yml
+# accelerate launch -m axolotl.cli.train ms-adventure.yml
+# python -m axolotl.cli.merge_lora ms-adventure.yml
+base_model: mistralai/Mistral-Small-Instruct-2409
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+sequence_len: 16384 # 99% vram
+min_sample_len: 128
+bf16: true
+fp16:
+tf32: false
+flash_attention: true
+special_tokens:
+# Data
+dataset_prepared_path: last_run_prepared
+datasets:
+  - path: ColumbidAI/adventure-ms-16k
+    type: completion
+warmup_steps: 20
+shuffle_merged_datasets: true
+save_safetensors: true
+# WandB
+wandb_project: Mistral-Small-Skein
+wandb_entity:
+# Iterations
+num_epochs: 1
+# Output
+output_dir: ./adventure-workspace
+hub_model_id: ToastyPigeon/mistral-small-adventure-qlora
+hub_strategy: "all_checkpoints"
+saves_per_epoch: 5
+# Sampling
+sample_packing: true
+pad_to_sequence_len: true
+# Batching
+gradient_accumulation_steps: 4
+micro_batch_size: 1
+eval_batch_size: 1
+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: 100
+evals_per_epoch: 5
+eval_table_size:
+eval_max_new_tokens: 256
+eval_sample_packing: false
+# 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:
+# Optimizer
+optimizer: paged_adamw_8bit # adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.0001
+cosine_min_lr_ratio: 0.1
+weight_decay: 0.01
+max_grad_norm: 10.0
+# 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:
+# Checkpoints
+resume_from_checkpoint:
+plugins:
+  - axolotl.integrations.liger.LigerPlugin
+liger_rope: true
+liger_rms_norm: true
+liger_swiglu: true
+liger_fused_linear_cross_entropy: true
+```
+</details><br>
+# mistral-small-adventure-qlora
+This model is a fine-tuned version of [mistralai/Mistral-Small-Instruct-2409](https://huggingface.co/mistralai/Mistral-Small-Instruct-2409) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9117
+## 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: 0.0001
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- total_eval_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 20
+- num_epochs: 1
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.8182        | 0.0035 | 1    | 2.1284          |
+| 1.8279        | 0.2043 | 59   | 1.9991          |
+| 1.8002        | 0.4087 | 118  | 1.9488          |
+| 1.7188        | 0.6130 | 177  | 1.9185          |
+| 1.7306        | 0.8173 | 236  | 1.9117          |
 ### Framework versions
+- PEFT 0.13.0
+- Transformers 4.45.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.20.0

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