ToastyPigeon
/

SpringDragon-NeMo-Instruct-QLoRA-ep1

@@ -1,202 +1,218 @@
 ---
-base_model: mistralai/Mistral-Nemo-Base-2407
 library_name: peft
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
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 ### Framework versions
-- PEFT 0.11.1

 ---
+base_model: mistralai/Mistral-Nemo-Instruct-2407
 library_name: peft
+license: apache-2.0
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: SpringDragon-NeMo-Instruct-QLoRA-ep1
+  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 download ToastyPigeon/SpringDragon-Instruct-v1-QLoRA-A --include checkpoint-210/* --local-dir .
+# python -m axolotl.cli.preprocess springdragon-nemo.yml
+# accelerate launch -m axolotl.cli.train springdragon-nemo.yml
+# Weights and Biases logging config
+wandb_project: SpringDragon-NeMo
+wandb_entity:
+wandb_watch:
+wandb_name:
+wandb_log_model:
+#eval_steps: 25
+#max_steps: 100
+#Model
+base_model: mistralai/Mistral-Nemo-Instruct-2407
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+# Hugging Face saving config
+hub_model_id: ToastyPigeon/SpringDragon-NeMo-Instruct-QLoRA-ep1
+hub_strategy: all_checkpoints
+push_dataset_to_hub:
+hf_use_auth_token:
+# Model checkpointing config
+output_dir: ./SpringDragon-NeMo
+resume_from_checkpoint:
+#save_steps: 100
+saves_per_epoch: 2
+save_safetensors: true
+save_total_limit: 3
+#
+bf16: auto
+fp16:
+tf32: false
+#
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+sequence_len: 2048
+pad_to_sequence_len: true
+sample_packing: true
+# Token config
+special_tokens:
+    pad_token: "<pad>"
+tokens:
+# Data
+datasets:
+  - path: BeaverAI/text_adventures
+    type: completion
+dataset_prepared_path: ./text_adventures
+val_set_size: 0.05
+evals_per_epoch: 20
+#evaluation_strategy: steps
+#eval_steps: 50
+eval_sample_packing: true
+# LoRA
+adapter: qlora
+lora_model_dir:
+lora_r: 64
+lora_alpha: 128
+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:
+# Unsloth stuff
+#unsloth_cross_entropy_loss: true
+#unsloth_lora_mlp: true
+#unsloth_lora_qkv: true
+#unsloth_lora_o: true
+# Other things
+#peft_use_dora: true
+# Training hyperparameters
+num_epochs: 1
+gradient_accumulation_steps: 1
+micro_batch_size: 6
+eval_batch_size: 6
+warmup_steps: 20
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.00003
+#loraplus_lr_ratio: 8
+#loraplus_lr_embedding:
+cosine_min_lr_ratio: 0.05
+weight_decay: 0.01
+max_grad_norm: 1.0
+logging_steps: 1
+# Model optimization
+#gradient_checkpointing: unsloth
+gradient_checkpointing: true
+xformers_attention: false
+flash_attention: true
+sdp_attention: false
+# Loss monitoring config
+early_stopping_patience: false
+loss_watchdog_threshold: 100.0
+loss_watchdog_patience: 3
+# Debug config
+debug: true
+seed: 111
+#Deepspeed
+#deepspeed: axolotl/deepspeed_configs/zero2.json
+# Don't mess with this, it's here for accelerate and torchrun
+local_rank:
+```
+</details><br>
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/lm-hall/SpringDragon-NeMo/runs/dghi0gyq)
+# SpringDragon-NeMo-Instruct-QLoRA-ep1
+This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2088
+## 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: 3e-05
+- train_batch_size: 6
+- eval_batch_size: 6
+- seed: 111
+- 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 |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.347         | 0.0017 | 1    | 2.3015          |
+| 2.306         | 0.0513 | 30   | 2.2631          |
+| 2.1792        | 0.1026 | 60   | 2.2356          |
+| 2.2576        | 0.1538 | 90   | 2.2298          |
+| 2.1577        | 0.2051 | 120  | 2.2236          |
+| 2.1493        | 0.2564 | 150  | 2.2221          |
+| 2.1297        | 0.3077 | 180  | 2.2232          |
+| 2.1284        | 0.3590 | 210  | 2.2174          |
+| 2.1102        | 0.4103 | 240  | 2.2126          |
+| 2.146         | 0.4615 | 270  | 2.2110          |
+| 2.2056        | 0.5128 | 300  | 2.2115          |
+| 2.2332        | 0.5641 | 330  | 2.2132          |
+| 2.0817        | 0.6154 | 360  | 2.2105          |
+| 2.1018        | 0.6667 | 390  | 2.2107          |
+| 2.0424        | 0.7179 | 420  | 2.2082          |
+| 2.1552        | 0.7692 | 450  | 2.2086          |
+| 2.2877        | 0.8205 | 480  | 2.2091          |
+| 2.191         | 0.8718 | 510  | 2.2090          |
+| 2.0968        | 0.9231 | 540  | 2.2090          |
+| 2.2092        | 0.9744 | 570  | 2.2088          |
 ### Framework versions
+- PEFT 0.11.1
+- Transformers 4.44.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1