End of training
Browse files- README.md +156 -0
- adapter_model.bin +3 -0
README.md
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---
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license: llama3
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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: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
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model-index:
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- name: taopanda-3_b49985cb-1972-4835-840c-c05792e5f494
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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: `0.4.1`
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```yaml
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adapter: lora
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base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0
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bf16: auto
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datasets:
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- data_files:
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- a11f8217f40ca211_train_data.json
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ds_type: json
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format: custom
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path: a11f8217f40ca211_train_data.json
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type:
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field: null
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field_input: null
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field_instruction: input
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field_output: response_a
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field_system: null
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format: null
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no_input_format: null
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system_format: '{system}'
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system_prompt: ''
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debug: null
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deepspeed: null
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early_stopping_patience: null
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eval_max_new_tokens: 128
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eval_sample_packing: false
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eval_table_size: null
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evals_per_epoch: 4
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flash_attention: true
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fp16: null
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps: 4
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gradient_checkpointing: true
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group_by_length: false
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hub_model_id: FatCat87/taopanda-3_b49985cb-1972-4835-840c-c05792e5f494
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learning_rate: 0.0002
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load_in_4bit: false
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load_in_8bit: true
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local_rank: null
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logging_steps: 1
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lora_alpha: 16
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lora_dropout: 0.05
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lora_r: 32
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lora_target_linear: true
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lr_scheduler: cosine
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micro_batch_size: 2
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model_type: AutoModelForCausalLM
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num_epochs: 2
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optimizer: adamw_bnb_8bit
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output_dir: ./outputs/out/taopanda-3_b49985cb-1972-4835-840c-c05792e5f494
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pad_to_sequence_len: true
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resume_from_checkpoint: null
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sample_packing: true
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saves_per_epoch: 1
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seed: 18127
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sequence_len: 4096
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special_tokens: null
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strict: false
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tf32: false
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tokenizer_type: AutoTokenizer
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train_on_inputs: false
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trust_remote_code: true
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val_set_size: 0.1
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wandb_entity: fatcat87-taopanda
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wandb_log_model: null
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wandb_mode: online
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wandb_name: taopanda-3_b49985cb-1972-4835-840c-c05792e5f494
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wandb_project: subnet56
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wandb_runid: taopanda-3_b49985cb-1972-4835-840c-c05792e5f494
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wandb_watch: null
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warmup_ratio: 0.05
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weight_decay: 0.0
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xformers_attention: null
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```
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</details><br>
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[<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/xp0sb7pk)
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# taopanda-3_b49985cb-1972-4835-840c-c05792e5f494
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This model is a fine-tuned version of [WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co/WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6800
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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: 2
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- eval_batch_size: 2
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- seed: 18127
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- total_eval_batch_size: 8
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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: 2
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.222 | 0.0396 | 1 | 1.2185 |
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| 0.9168 | 0.2772 | 7 | 0.8508 |
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| 0.7745 | 0.5545 | 14 | 0.7478 |
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| 0.7129 | 0.8317 | 21 | 0.7133 |
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| 0.7005 | 1.0792 | 28 | 0.6945 |
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| 0.6863 | 1.3564 | 35 | 0.6855 |
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| 0.6688 | 1.6337 | 42 | 0.6808 |
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| 0.6772 | 1.9109 | 49 | 0.6800 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.42.3
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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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 sha256:2308466c05a81d7bb706ae0e06a8b7801259199bf126889474140df345521a4d
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size 335706186
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