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Mistral-7B_task-1_120-samples_config-2_auto

PEFT
TensorBoard
Safetensors
mistral
alignment-handbook
trl
sft
Generated from Trainer
4-bit precision
bitsandbytes
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  1. README.md +75 -0
  2. adapter_model.safetensors +1 -1
  3. all_results.json +9 -0
  4. train_results.json +9 -0
  5. trainer_state.json +356 -0
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+ ---
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+ base_model: mistralai/Mistral-7B-Instruct-v0.3
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+ library_name: peft
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+ license: apache-2.0
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+ tags:
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+ - trl
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+ - sft
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+ - generated_from_trainer
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+ model-index:
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+ - name: Mistral-7B_task-1_120-samples_config-2_auto
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+ results: []
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+ ---
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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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+
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+ # Mistral-7B_task-1_120-samples_config-2_auto
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+
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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 None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.4895
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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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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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 16
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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_ratio: 0.1
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:----:|:---------------:|
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+ | 1.0732 | 0.9091 | 5 | 1.0410 |
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+ | 0.9533 | 2.0 | 11 | 0.8652 |
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+ | 0.77 | 2.9091 | 16 | 0.8181 |
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+ | 0.6091 | 4.0 | 22 | 0.8006 |
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+ | 0.4937 | 4.9091 | 27 | 0.8277 |
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+ | 0.3093 | 6.0 | 33 | 0.9964 |
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+ | 0.1731 | 6.9091 | 38 | 1.0815 |
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+ | 0.1045 | 8.0 | 44 | 1.3044 |
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+ | 0.0642 | 8.9091 | 49 | 1.3456 |
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+ | 0.0552 | 10.0 | 55 | 1.4001 |
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+ | 0.0359 | 10.9091 | 60 | 1.4895 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.44.0
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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