End of training
Browse files- README.md +166 -3
- adapter_model.bin +3 -0
README.md
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---
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license:
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---
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license: llama2
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library_name: peft
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tags:
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- axolotl
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- generated_from_trainer
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base_model: codellama/CodeLlama-7b-hf
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model-index:
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- name: EvilCodeLlama-7b
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<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)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.3.0`
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```yaml
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base_model: codellama/CodeLlama-7b-hf
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base_model_config: codellama/CodeLlama-7b-hf
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model_type: LlamaForCausalLM
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tokenizer_type: LlamaTokenizer
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is_llama_derived_model: true
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hub_model_id: EvilCodeLlama-7b
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load_in_8bit: false
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load_in_4bit: true
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strict: false
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datasets:
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- path: dhuynh95/Magicoder-Evol-Instruct-110K-Filtered_0.35
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.02
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output_dir: ./qlora-out-evil-codellama
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adapter: qlora
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lora_model_dir:
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eval_sample_packing: false
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sequence_len: 2048
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sample_packing: true
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lora_r: 32
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_modules:
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lora_target_linear: true
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lora_fan_in_fan_out:
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wandb_project: axolotl
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wandb_entity:
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wandb_watch:
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wandb_run_id:
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wandb_log_model:
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gradient_accumulation_steps: 4
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micro_batch_size: 16
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num_epochs: 1
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optimizer: paged_adamw_32bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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train_on_inputs: true
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group_by_length: false
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bf16: true
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fp16: false
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tf32: false
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gradient_checkpointing: true
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early_stopping_patience:
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resume_from_checkpoint:
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local_rank:
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logging_steps: 1
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xformers_attention:
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flash_attention: true
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warmup_steps: 100
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eval_steps: 0.01
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save_strategy: epoch
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save_steps:
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debug:
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deepspeed:
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weight_decay: 0.0
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fsdp:
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fsdp_config:
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special_tokens:
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bos_token: "<s>"
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eos_token: "</s>"
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unk_token: "<unk>"
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```
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</details><br>
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# EvilCodeLlama-7b
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This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1701
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.2543 | 0.04 | 1 | 1.2447 |
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| 1.2781 | 0.08 | 2 | 1.2445 |
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| 1.2677 | 0.12 | 3 | 1.2446 |
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| 1.2725 | 0.16 | 4 | 1.2447 |
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| 1.2704 | 0.21 | 5 | 1.2440 |
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| 1.2572 | 0.25 | 6 | 1.2442 |
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| 1.2875 | 0.29 | 7 | 1.2439 |
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| 1.2672 | 0.33 | 8 | 1.2434 |
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| 1.2601 | 0.37 | 9 | 1.2430 |
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| 1.2808 | 0.41 | 10 | 1.2421 |
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| 1.2665 | 0.45 | 11 | 1.2411 |
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| 1.2572 | 0.49 | 12 | 1.2400 |
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| 1.2505 | 0.54 | 13 | 1.2384 |
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| 1.264 | 0.58 | 14 | 1.2365 |
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| 1.2809 | 0.62 | 15 | 1.2338 |
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| 1.2054 | 0.66 | 16 | 1.2308 |
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| 1.2732 | 0.7 | 17 | 1.2269 |
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| 1.2586 | 0.74 | 18 | 1.2219 |
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| 1.2939 | 0.78 | 19 | 1.2161 |
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| 1.2713 | 0.82 | 20 | 1.2086 |
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| 1.2154 | 0.87 | 21 | 1.2008 |
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| 1.213 | 0.91 | 22 | 1.1917 |
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| 1.2183 | 0.95 | 23 | 1.1813 |
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| 1.1594 | 0.99 | 24 | 1.1701 |
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### Framework versions
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- PEFT 0.7.2.dev0
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- Transformers 4.37.0.dev0
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- Pytorch 2.0.1+cu117
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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adapter_model.bin
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:d5b9a26a33e771dccdf87643e0178fbfd3b69a586d451c8717a58550fe19b964
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size 319977229
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