ToastyPigeon
/

mistral-small-adventure-qlora

@@ -9,186 +9,4 @@ 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

 - name: mistral-small-adventure-qlora
   results: []
 ---
+Mistral Small Instruct on Spring Dragon + Skein adventure dataset.