rkreddyp
/

NistCodeLlama-7b

+---
+license: apache-2.0
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-v0.1
+model-index:
+- name: NistCodeLlama-7b
+  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: `0.4.0`
+```yaml
+base_model: mistralai/Mistral-7B-v0.1
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_llama_derived_model: true
+hub_model_id: NistCodeLlama-7b
+sample_packing: false
+eval_sample_packing: false
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+datasets:
+  - path: rkreddyp/nist_800_53
+    ds_type: json
+    type:
+              field_instruction: question
+              field_input: context
+              field_output: answer
+              format: |-
+                [INST] Using the schema context below, generate a SQL query that answers the question.
+                {input}
+                {instruction} [/INST]
+dataset_prepared_path:
+val_set_size: 0.02
+output_dir: ./qlora-out
+adapter: qlora
+lora_model_dir:
+sequence_len: 2048
+sample_packing: true
+lora_r: 32
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules:
+lora_target_linear: true
+lora_fan_in_fan_out:
+wandb_project: axolotl-nist
+wandb_entity:
+wandb_watch:
+wandb_run_id:
+wandb_log_model:
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 3
+optimizer: paged_adamw_32bit
+lr_scheduler: cosine
+learning_rate: 0.0002
+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
+warmup_steps: 100
+eval_steps: 0.01
+save_strategy: epoch
+save_steps:
+debug:
+deepspeed:
+weight_decay: 0.0
+fsdp:
+fsdp_config:
+special_tokens:
+  bos_token: "<s>"
+  eos_token: "</s>"
+  unk_token: "<unk>"
+```
+</details><br>
+# NistCodeLlama-7b
+This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3414
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 3
+### Training results
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.4855        | 0.06  | 1    | 1.4808          |
+| 1.4522        | 0.11  | 2    | 1.4811          |
+| 1.4616        | 0.17  | 3    | 1.4788          |
+| 1.5276        | 0.23  | 4    | 1.4746          |
+| 1.4564        | 0.29  | 5    | 1.4662          |
+| 1.4837        | 0.34  | 6    | 1.4515          |
+| 1.4709        | 0.4   | 7    | 1.4280          |
+| 1.3571        | 0.46  | 8    | 1.3903          |
+| 1.4164        | 0.51  | 9    | 1.3363          |
+| 1.3257        | 0.57  | 10   | 1.2692          |
+| 1.2858        | 0.63  | 11   | 1.2027          |
+| 1.2318        | 0.69  | 12   | 1.1364          |
+| 1.1164        | 0.74  | 13   | 1.0595          |
+| 1.0984        | 0.8   | 14   | 0.9748          |
+| 0.9593        | 0.86  | 15   | 0.8923          |
+| 0.8325        | 0.91  | 16   | 0.8137          |
+| 0.8357        | 0.97  | 17   | 0.7426          |
+| 0.6483        | 1.03  | 18   | 0.6868          |
+| 0.7138        | 1.06  | 19   | 0.6400          |
+| 0.6105        | 1.11  | 20   | 0.6027          |
+| 0.6409        | 1.17  | 21   | 0.5686          |
+| 0.5206        | 1.23  | 22   | 0.5317          |
+| 0.521         | 1.29  | 23   | 0.4962          |
+| 0.4409        | 1.34  | 24   | 0.4697          |
+| 0.4678        | 1.4   | 25   | 0.4481          |
+| 0.3731        | 1.46  | 26   | 0.4303          |
+| 0.388         | 1.51  | 27   | 0.4161          |
+| 0.3463        | 1.57  | 28   | 0.4085          |
+| 0.3699        | 1.63  | 29   | 0.4035          |
+| 0.3673        | 1.69  | 30   | 0.3992          |
+| 0.4485        | 1.74  | 31   | 0.3962          |
+| 0.3855        | 1.8   | 32   | 0.3929          |
+| 0.3249        | 1.86  | 33   | 0.3887          |
+| 0.3528        | 1.91  | 34   | 0.3839          |
+| 0.372         | 1.97  | 35   | 0.3801          |
+| 0.3922        | 2.03  | 36   | 0.3768          |
+| 0.3783        | 2.06  | 37   | 0.3739          |
+| 0.31          | 2.11  | 38   | 0.3721          |
+| 0.275         | 2.17  | 39   | 0.3699          |
+| 0.338         | 2.23  | 40   | 0.3665          |
+| 0.3238        | 2.29  | 41   | 0.3633          |
+| 0.3382        | 2.34  | 42   | 0.3597          |
+| 0.3467        | 2.4   | 43   | 0.3567          |
+| 0.3494        | 2.46  | 44   | 0.3541          |
+| 0.3431        | 2.51  | 45   | 0.3533          |
+| 0.3433        | 2.57  | 46   | 0.3522          |
+| 0.304         | 2.63  | 47   | 0.3491          |
+| 0.3098        | 2.69  | 48   | 0.3464          |
+| 0.279         | 2.74  | 49   | 0.3443          |
+| 0.3105        | 2.8   | 50   | 0.3425          |
+| 0.2305        | 2.86  | 51   | 0.3414          |
+### Framework versions
+- PEFT 0.8.2
+- Transformers 4.38.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.15.0

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