Create README.md

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-v0.3
+model-index:
+- name: mistral-sql-create-context-lora
+  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+base_model: mistralai/Mistral-7B-v0.3
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+
+load_in_8bit: false
+load_in_4bit: false
+strict: false
+
+datasets:
+  - path: b-mc2/sql-create-context
+    type:
+      # JSONL file contains question, context, answer fields per line.
+      # This gets mapped to instruction, input, output axolotl tags.
+      field_instruction: question
+      field_input: context
+      field_output: answer
+      # Format is used by axolotl to generate the prompt.
+      format: |-
+        [INST] Using the schema context below, generate a SQL query that answers the question.
+        {input}
+        {instruction} [/INST]
+
+tokens: # add new control tokens from the dataset to the model
+  - "[INST]"
+  - " [/INST]"
+  - "[SQL]"
+  - " [/SQL]"
+    
+dataset_prepared_path:
+val_set_size: 0.05
+output_dir: ./outputs/mistral-sql-create-context-lora
+hub_model_id: ahmedsamirio/mistral-sql-create-context-lora
+
+# This is set to 4096 in the modal config, why?
+# Since I'm using sample packing, decreasing the sequence length will create smaller batches
+# which can fit better into memory
+sequence_len: 8192
+
+# These is set to false in the modal example, why? (Modal also uses FSDP which might be a reason)
+sample_packing: true
+eval_sample_packing: true
+pad_to_sequence_len: true
+
+adapter: lora
+lora_model_dir:
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+lora_fan_in_fan_out:
+
+lora_modules_to_save: # required when adding new tokens to LLaMA/Mistral
+  - embed_tokens
+  - lm_head
+  
+lora_target_modules:
+  - gate_proj
+  - down_proj
+  - up_proj
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+
+wandb_project: mistral-sql-create-context
+wandb_entity: ahmedsamirio
+wandb_watch:
+wandb_name:
+wandb_log_model:
+
+gradient_accumulation_steps: 2
+micro_batch_size: 4
+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
+
+# What is this?
+loss_watchdog_threshold: 5.0
+loss_watchdog_patience: 3
+
+warmup_steps: 10
+evals_per_epoch: 4
+eval_table_size:
+
+# This wasn't set in modal config
+
+eval_max_new_tokens: 128
+saves_per_epoch: 1
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+```
+
+</details>