AiAF
/

Pretraining-SCPWiki-032025-7B-Instruct

@@ -1,202 +1,176 @@
 ---
-base_model: mistralai/Mistral-7B-Instruct-v0.3
 library_name: peft
 ---
-# Model Card for Model ID
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-## Model Details
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 ### Framework versions
-- PEFT 0.14.0

 ---
 library_name: peft
+license: apache-2.0
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+tags:
+- axolotl
+- generated_from_trainer
+datasets:
+- AiAF/Pretraining-SCPWiki-032025-7B-Instruct-pretraining.jsonl
+model-index:
+- name: Pretraining-SCPWiki-032025-7B-Instruct
+  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: `0.8.0.dev0`
+```yaml
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+# optionally might have model_type or tokenizer_type
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+# Automatically upload checkpoint and final model to HF
+hub_model_id: AiAF/Pretraining-SCPWiki-032025-7B-Instruct
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+datasets:
+  - path: AiAF/Pretraining-SCPWiki-032025-7B-Instruct-pretraining.jsonl
+   # type: completion
+   # text_column: text # column in dataset with the data, usually `text`
+    type: completion
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.1
+output_dir: ./outputs/qlora-out/Pretraining-SCPWiki-032025-7B-Instruct-V1
+adapter: qlora
+lora_model_dir:
+sequence_len: 8192
+sample_packing: true
+pad_to_sequence_len: true
+lora_r: 16
+lora_alpha: 32
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+wandb_project: "LLM-Pretraining"
+wandb_entity:
+wandb_watch: "all"
+wandb_name: "Pretraining-SCPWiki-032025-7B-Instruct-V1"
+wandb_log_model: "false"
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 1
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+train_on_inputs: false
+group_by_length: false
+bf16: auto
+fp16:
+tf32: false
+gradient_checkpointing: true
+early_stopping_patience:
+resume_from_checkpoint:
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+loss_watchdog_threshold: 5.0
+loss_watchdog_patience: 3
+warmup_steps: 10
+evals_per_epoch: 20
+eval_table_size:
+eval_max_new_tokens: 128
+saves_per_epoch: 20
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+```
+</details><br>
+# Pretraining-SCPWiki-032025-7B-Instruct
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the AiAF/Pretraining-SCPWiki-032025-7B-Instruct-pretraining.jsonl dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5048
+## 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: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 1.0
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.0192        | 0.0016 | 1    | 1.9469          |
+| 1.3794        | 0.0509 | 32   | 1.5979          |
+| 1.5383        | 0.1019 | 64   | 1.5626          |
+| 1.3583        | 0.1528 | 96   | 1.5544          |
+| 1.3354        | 0.2037 | 128  | 1.5393          |
+| 1.4771        | 0.2547 | 160  | 1.5319          |
+| 1.4542        | 0.3056 | 192  | 1.5262          |
+| 1.2767        | 0.3565 | 224  | 1.5228          |
+| 1.3347        | 0.4075 | 256  | 1.5202          |
+| 1.4451        | 0.4584 | 288  | 1.5169          |
+| 1.1028        | 0.5094 | 320  | 1.5147          |
+| 1.315         | 0.5603 | 352  | 1.5126          |
+| 1.3244        | 0.6112 | 384  | 1.5106          |
+| 1.3915        | 0.6622 | 416  | 1.5089          |
+| 1.3156        | 0.7131 | 448  | 1.5077          |
+| 1.2967        | 0.7640 | 480  | 1.5067          |
+| 1.4046        | 0.8150 | 512  | 1.5056          |
+| 1.4017        | 0.8659 | 544  | 1.5052          |
+| 1.2678        | 0.9168 | 576  | 1.5050          |
+| 1.231         | 0.9678 | 608  | 1.5048          |
 ### Framework versions
+- PEFT 0.14.0
+- Transformers 4.49.0
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0