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--- |
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license: cc-by-nc-4.0 |
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base_model: lightblue/suzume-llama-3-8B-multilingual |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: >- |
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workspace/llm_training/axolotl/llama3-multilingual-orpo/output_mitsu_half_borda |
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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: `0.4.0` |
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```yaml |
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base_model: lightblue/suzume-llama-3-8B-multilingual |
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model_type: LlamaForCausalLM |
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tokenizer_type: AutoTokenizer # PreTrainedTokenizerFast |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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rl: orpo |
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orpo_alpha: 0.1 |
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remove_unused_columns: false |
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chat_template: chatml |
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datasets: |
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- path: lightblue/mitsu_tophalf_borda |
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type: orpo.chat_template |
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conversation: llama-3 |
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dataset_prepared_path: /workspace/llm_training/axolotl/llama3-multilingual-orpo/prepared_mitsu_half_borda |
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val_set_size: 0.02 |
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output_dir: /workspace/llm_training/axolotl/llama3-multilingual-orpo/output_mitsu_half_borda |
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sequence_len: 8192 |
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sample_packing: false |
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pad_to_sequence_len: true |
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use_wandb: true |
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wandb_project: axolotl |
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wandb_entity: peterd |
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wandb_name: mitsu_half_borda |
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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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num_epochs: 1 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 8e-6 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: true |
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gradient_checkpointing_kwargs: |
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use_reentrant: false |
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early_stopping_patience: |
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resume_from_checkpoint: |
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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: 10 |
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evals_per_epoch: 20 |
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eval_table_size: |
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saves_per_epoch: 1 |
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debug: |
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deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.0 |
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special_tokens: |
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pad_token: <|end_of_text|> |
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``` |
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</details><br> |
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# workspace/llm_training/axolotl/llama3-multilingual-orpo/output_mitsu_half_borda |
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This model is a fine-tuned version of [lightblue/suzume-llama-3-8B-multilingual](https://huggingface.co/lightblue/suzume-llama-3-8B-multilingual) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0935 |
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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: 8e-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 4 |
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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: 10 |
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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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| 7.6299 | 0.02 | 1 | 7.7014 | |
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| 7.041 | 0.07 | 3 | 3.9786 | |
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| 0.6089 | 0.15 | 6 | 0.1393 | |
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| 0.1308 | 0.22 | 9 | 0.1244 | |
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| 0.1051 | 0.29 | 12 | 0.1112 | |
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| 0.1021 | 0.36 | 15 | 0.1063 | |
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| 0.0861 | 0.44 | 18 | 0.1026 | |
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| 0.1031 | 0.51 | 21 | 0.0979 | |
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| 0.0996 | 0.58 | 24 | 0.0967 | |
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| 0.0923 | 0.65 | 27 | 0.0960 | |
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| 0.1025 | 0.73 | 30 | 0.0944 | |
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| 0.1103 | 0.8 | 33 | 0.0939 | |
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| 0.0919 | 0.87 | 36 | 0.0937 | |
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| 0.104 | 0.94 | 39 | 0.0935 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.0 |
