End of training

README.md

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+---
+library_name: peft
+tags:
+- axolotl
+- generated_from_trainer
+base_model: NousResearch/CodeLlama-13b-hf
+model-index:
+- name: f9e002e8-3c9b-446b-9fc8-c6d690ef84fb
+  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
+adapter: lora
+base_model: NousResearch/CodeLlama-13b-hf
+bf16: auto
+datasets:
+- data_files:
+  - 1fd2a762c9d13cae_train_data.json
+  ds_type: json
+  format: custom
+  path: 1fd2a762c9d13cae_train_data.json
+  type:
+    field: null
+    field_input: text
+    field_instruction: intent
+    field_output: slots
+    field_system: null
+    format: null
+    no_input_format: null
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+deepspeed: null
+early_stopping_patience: null
+eval_max_new_tokens: 128
+eval_sample_packing: false
+eval_table_size: null
+evals_per_epoch: 2
+flash_attention: true
+fp16: null
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 4
+gradient_checkpointing: true
+group_by_length: false
+hub_model_id: taopanda/f9e002e8-3c9b-446b-9fc8-c6d690ef84fb
+learning_rate: 0.0002
+load_in_4bit: false
+load_in_8bit: true
+local_rank: null
+logging_steps: 1
+lora_alpha: 16
+lora_dropout: 0.05
+lora_r: 32
+lora_target_linear: true
+lr_scheduler: cosine
+micro_batch_size: 2
+model_type: AutoModelForCausalLM
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+output_dir: ./outputs/out/taopanda-3_4bea4578-524c-4430-8071-bbcf24df00eb
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+sample_packing: true
+saves_per_epoch: 1
+seed: 36843
+sequence_len: 4096
+special_tokens:
+  pad_token: </s>
+strict: false
+tf32: false
+tokenizer_type: AutoTokenizer
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0.1
+wandb_entity: fatcat87-taopanda
+wandb_log_model: null
+wandb_mode: online
+wandb_name: taopanda-3_4bea4578-524c-4430-8071-bbcf24df00eb
+wandb_project: subnet56
+wandb_runid: taopanda-3_4bea4578-524c-4430-8071-bbcf24df00eb
+wandb_watch: null
+warmup_ratio: 0.05
+weight_decay: 0.0
+xformers_attention: null
+
+```
+
+</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/fatcat87-taopanda/subnet56/runs/h2uor2n9)
+# f9e002e8-3c9b-446b-9fc8-c6d690ef84fb
+
+This model is a fine-tuned version of [NousResearch/CodeLlama-13b-hf](https://huggingface.co/NousResearch/CodeLlama-13b-hf) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.8077
+
+## 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: 36843
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 4.7213        | 0.5   | 1    | 2.8201          |
+| 4.4683        | 1.0   | 2    | 2.8068          |
+| 3.6748        | 1.375 | 3    | 2.8065          |
+| 3.0455        | 1.875 | 4    | 2.8077          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.42.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

adapter_model.bin

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