End of training

README.md

@@ -1,3 +1,194 @@
----
-license: apache-2.0
----
+---
+base_model: Qwen/CodeQwen1.5-7B-Chat
+library_name: peft
+license: other
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: CodeQwen1.5-7B-Chat-lora8-NLQ2Cypher
+  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: deepseek-ai/deepseek-coder-1.3b-instruct
+base_model: Qwen/CodeQwen1.5-7B-Chat
+model_type: AutoModelForCausalLM
+tokenizer_type: AutoTokenizer
+is_mistral_derived_model: false
+
+load_in_8bit: true
+load_in_4bit: false
+strict: false
+
+lora_fan_in_fan_out: false
+data_seed: 49
+seed: 49
+
+datasets:
+  - path: sample_data/alpaca_synth_cypher.jsonl
+    type: sharegpt
+    conversation: alpaca
+dataset_prepared_path: last_run_prepared
+val_set_size: 0.1
+output_dir: ./qlora-alpaca-codeqwen1.5-7b-chat-lora8
+# output_dir: ./qlora-alpaca-out
+
+hub_model_id: jermyn/CodeQwen1.5-7B-Chat-lora8-NLQ2Cypher
+# hub_model_id: jermyn/deepseek-code-1.3b-inst-NLQ2Cypher
+
+adapter: lora   # 'qlora' or leave blank for full finetune
+lora_model_dir:
+
+sequence_len: 896
+sample_packing: false
+pad_to_sequence_len: true
+
+lora_r: 32
+lora_alpha: 16
+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
+
+# If you added new tokens to the tokenizer, you may need to save some LoRA modules because they need to know the new tokens.
+# For LLaMA and Mistral, you need to save `embed_tokens` and `lm_head`. It may vary for other models.
+# `embed_tokens` converts tokens to embeddings, and `lm_head` converts embeddings to token probabilities.
+# https://github.com/huggingface/peft/issues/334#issuecomment-1561727994
+# lora_modules_to_save:
+#   - embed_tokens
+#   - lm_head
+
+wandb_project: fine-tune-axolotl
+wandb_entity: jermyn
+
+gradient_accumulation_steps: 2
+micro_batch_size: 8
+eval_batch_size: 8
+num_epochs: 6
+optimizer: adamw_bnb_8bit
+lr_scheduler: cosine
+learning_rate: 0.0005
+max_grad_norm: 1.0
+adam_beta2: 0.95
+adam_epsilon: 0.00001
+
+train_on_inputs: false
+group_by_length: false
+bf16: true
+fp16: false
+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: 4
+eval_table_size:
+eval_table_max_new_tokens: 128
+# saves_per_epoch: 6
+save_steps: 10
+save_total_limit: 3
+debug:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+# special_tokens:
+#   bos_token: "<s>"
+#   eos_token: "</s>"
+#   unk_token: "<unk>"
+save_safetensors: true
+
+```
+
+</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/jermyn/fine-tune-axolotl/runs/jmysluep)
+# CodeQwen1.5-7B-Chat-lora8-NLQ2Cypher
+
+This model is a fine-tuned version of [Qwen/CodeQwen1.5-7B-Chat](https://huggingface.co/Qwen/CodeQwen1.5-7B-Chat) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3720
+
+## 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: 0.0005
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 49
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.1649        | 0.1538 | 1    | 0.9270          |
+| 1.1566        | 0.3077 | 2    | 0.9268          |
+| 1.0746        | 0.6154 | 4    | 0.8194          |
+| 0.6428        | 0.9231 | 6    | 0.4970          |
+| 0.2459        | 1.2308 | 8    | 0.4760          |
+| 0.3512        | 1.5385 | 10   | 0.5091          |
+| 0.1654        | 1.8462 | 12   | 0.4742          |
+| 0.1484        | 2.1538 | 14   | 0.4560          |
+| 0.137         | 2.4615 | 16   | 0.4105          |
+| 0.0746        | 2.7692 | 18   | 0.3736          |
+| 0.0539        | 3.0769 | 20   | 0.3412          |
+| 0.1147        | 3.3846 | 22   | 0.3307          |
+| 0.056         | 3.6923 | 24   | 0.3242          |
+| 0.0767        | 4.0    | 26   | 0.3524          |
+| 0.0583        | 4.3077 | 28   | 0.3690          |
+| 0.0666        | 4.6154 | 30   | 0.3727          |
+| 0.0539        | 4.9231 | 32   | 0.3773          |
+| 0.0367        | 5.2308 | 34   | 0.3796          |
+| 0.0297        | 5.5385 | 36   | 0.3720          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.42.3
+- Pytorch 2.1.2+cu118
+- Datasets 2.19.1
+- Tokenizers 0.19.1