End of training
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- adapter_model.bin +1 -1
README.md
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license: apache-2.0
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: mistralai/Mistral-7B-v0.3
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model-index:
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- name:
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results: []
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---
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strict: false
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datasets:
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- path:
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.
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output_dir: ./outputs/lora-out
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adapter: lora
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lora_model_dir:
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sequence_len:
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sample_packing: false
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pad_to_sequence_len: true
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lora_r:
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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wandb_project: axolotl-runs
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wandb_entity: thewind-mom-finetuning
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wandb_watch:
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wandb_name: Mistral-7B-v0.3-
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wandb_log_model:
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gradient_accumulation_steps: 4
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micro_batch_size:
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num_epochs:
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optimizer:
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lr_scheduler: cosine
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learning_rate: 0.0002
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</details><br>
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#
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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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:
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- eval_batch_size:
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 3
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- gradient_accumulation_steps: 4
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- total_train_batch_size:
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- total_eval_batch_size:
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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:
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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.
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| 0.
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| 0.
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### Framework versions
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license: apache-2.0
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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: mistralai/Mistral-7B-v0.3
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model-index:
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- name: Mistral-7B-v0.3-deide-phi
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results: []
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---
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strict: false
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datasets:
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- path: thewimo/german-medical-identification-dataset-v0.1
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type: alpaca
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dataset_prepared_path: last_run_prepared
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val_set_size: 0.2
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output_dir: ./outputs/lora-out
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hub_model_id: thewimo/Mistral-7B-v0.3-deide-phi
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adapter: lora
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lora_model_dir:
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sequence_len: 4096
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sample_packing: false
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pad_to_sequence_len: true
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lora_r: 8
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lora_alpha: 16
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lora_dropout: 0.05
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lora_target_linear: true
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wandb_project: axolotl-runs
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wandb_entity: thewind-mom-finetuning
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wandb_watch:
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wandb_name: Mistral-7B-v0.3-deide-phi
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wandb_log_model:
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gradient_accumulation_steps: 4
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micro_batch_size: 4
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num_epochs: 4
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optimizer: paged_adamw_8bit
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lr_scheduler: cosine
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learning_rate: 0.0002
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</details><br>
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# Mistral-7B-v0.3-deide-phi
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0364
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## Model description
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 3
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 48
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- total_eval_batch_size: 12
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 1.9682 | 0.0506 | 1 | 2.0579 |
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| 1.2784 | 0.2532 | 5 | 0.8308 |
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| 0.187 | 0.5063 | 10 | 0.1732 |
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| 0.1094 | 0.7595 | 15 | 0.0819 |
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| 0.0542 | 1.0127 | 20 | 0.0593 |
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| 0.0354 | 1.2658 | 25 | 0.0521 |
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| 0.0493 | 1.5190 | 30 | 0.0457 |
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| 0.038 | 1.7722 | 35 | 0.0432 |
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| 0.0143 | 2.0253 | 40 | 0.0425 |
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| 0.0269 | 2.2785 | 45 | 0.0423 |
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| 0.0273 | 2.5316 | 50 | 0.0415 |
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| 0.0277 | 2.7848 | 55 | 0.0366 |
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| 0.0288 | 3.0380 | 60 | 0.0356 |
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| 0.0241 | 3.2911 | 65 | 0.0358 |
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| 0.0125 | 3.5443 | 70 | 0.0362 |
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| 0.0164 | 3.7975 | 75 | 0.0364 |
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### Framework versions
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adapter_model.bin
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version https://git-lfs.github.com/spec/v1
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size 84047370
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version https://git-lfs.github.com/spec/v1
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size 84047370
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