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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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tags: |
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- axolotl |
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- generated_from_trainer |
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datasets: |
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- json |
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model-index: |
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- name: Pretraining-SpongeBoB-7B-Instruct-V1 |
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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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.8.0.dev0` |
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```yaml |
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base_model: mistralai/Mistral-7B-Instruct-v0.3 |
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# optionally might have model_type or tokenizer_type |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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# Automatically upload checkpoint and final model to HF |
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hub_model_id: AiAF/Pretraining-SpongeBoB-7B-Instruct-V1 |
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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: json |
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data_files: [pretraining.jsonl] |
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type: completion |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.1 |
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output_dir: ./outputs/qlora-out/Pretraining-SpongeBoB-7B-Instruct-V1 |
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save_total_limit: 10 |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 8192 |
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sample_packing: true |
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pad_to_sequence_len: true |
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lora_r: 256 |
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lora_alpha: 64 |
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lora_dropout: 0.05 |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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lora_target_modules: |
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- gate_proj |
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- down_proj |
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- up_proj |
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- q_proj |
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- v_proj |
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- k_proj |
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- o_proj |
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wandb_project: "LLM-Pretraining" |
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wandb_entity: |
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wandb_watch: "all" |
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wandb_name: "Pretraining-SpongeBoB-7B-Instruct-V1" |
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wandb_run_id: "Pretraining-SpongeBoB-7B-Instruct-V1" |
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wandb_log_model: "false" |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 9 |
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num_epochs: 10 |
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optimizer: adamw_bnb_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000005 |
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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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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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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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warmup_steps: 10 |
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evals_per_epoch: 5 |
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eval_table_size: |
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eval_max_new_tokens: 128 |
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saves_per_epoch: 5 |
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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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``` |
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</details><br> |
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# Pretraining-SpongeBoB-7B-Instruct-V1 |
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the json dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6255 |
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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: 5e-06 |
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- train_batch_size: 9 |
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- eval_batch_size: 9 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 18 |
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- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.7843 | 0.0417 | 1 | 1.7939 | |
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| 1.8262 | 0.2083 | 5 | 1.7915 | |
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| 1.839 | 0.4167 | 10 | 1.7733 | |
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| 1.7503 | 0.625 | 15 | 1.7438 | |
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| 1.7191 | 0.8333 | 20 | 1.7260 | |
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| 1.7191 | 1.0417 | 25 | 1.7138 | |
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| 1.7548 | 1.25 | 30 | 1.7023 | |
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| 1.6795 | 1.4583 | 35 | 1.6924 | |
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| 1.6848 | 1.6667 | 40 | 1.6836 | |
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| 1.6856 | 1.875 | 45 | 1.6770 | |
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| 1.7155 | 2.0833 | 50 | 1.6715 | |
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| 1.6901 | 2.2917 | 55 | 1.6665 | |
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| 1.6797 | 2.5 | 60 | 1.6621 | |
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| 1.6704 | 2.7083 | 65 | 1.6581 | |
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| 1.6763 | 2.9167 | 70 | 1.6545 | |
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| 1.678 | 3.125 | 75 | 1.6516 | |
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| 1.6271 | 3.3333 | 80 | 1.6490 | |
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| 1.662 | 3.5417 | 85 | 1.6468 | |
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| 1.6384 | 3.75 | 90 | 1.6446 | |
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| 1.6273 | 3.9583 | 95 | 1.6427 | |
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| 1.5934 | 4.1667 | 100 | 1.6408 | |
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| 1.6217 | 4.375 | 105 | 1.6393 | |
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| 1.6383 | 4.5833 | 110 | 1.6378 | |
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| 1.6244 | 4.7917 | 115 | 1.6365 | |
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| 1.6238 | 5.0 | 120 | 1.6352 | |
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| 1.6179 | 5.2083 | 125 | 1.6340 | |
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| 1.6203 | 5.4167 | 130 | 1.6330 | |
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| 1.6177 | 5.625 | 135 | 1.6319 | |
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| 1.6332 | 5.8333 | 140 | 1.6310 | |
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| 1.6277 | 6.0417 | 145 | 1.6302 | |
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| 1.6461 | 6.25 | 150 | 1.6296 | |
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| 1.6668 | 6.4583 | 155 | 1.6290 | |
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| 1.6249 | 6.6667 | 160 | 1.6284 | |
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| 1.6013 | 6.875 | 165 | 1.6278 | |
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| 1.6098 | 7.0833 | 170 | 1.6274 | |
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| 1.5954 | 7.2917 | 175 | 1.6270 | |
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| 1.6488 | 7.5 | 180 | 1.6267 | |
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| 1.6153 | 7.7083 | 185 | 1.6264 | |
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| 1.6232 | 7.9167 | 190 | 1.6262 | |
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| 1.6611 | 8.125 | 195 | 1.6260 | |
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| 1.5997 | 8.3333 | 200 | 1.6258 | |
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| 1.6166 | 8.5417 | 205 | 1.6258 | |
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| 1.6427 | 8.75 | 210 | 1.6256 | |
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| 1.6157 | 8.9583 | 215 | 1.6255 | |
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| 1.6303 | 9.1667 | 220 | 1.6255 | |
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| 1.6179 | 9.375 | 225 | 1.6255 | |
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| 1.6063 | 9.5833 | 230 | 1.6255 | |
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| 1.6043 | 9.7917 | 235 | 1.6255 | |
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| 1.5881 | 10.0 | 240 | 1.6255 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.49.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
