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Ashish1920/ashishgpt-ft

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README.md ADDED
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+ ---
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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: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
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+ model-index:
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+ - name: shawgpt-ft
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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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+ # shawgpt-ft
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+
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+ This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.3791
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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: 0.0002
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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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+ - gradient_accumulation_steps: 4
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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: linear
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+ - lr_scheduler_warmup_steps: 2
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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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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+ | 5.2488 | 0.96 | 6 | 4.7586 |
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+ | 4.7253 | 1.92 | 12 | 4.3709 |
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+ | 4.4109 | 2.88 | 18 | 4.1224 |
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+ | 3.5231 | 4.0 | 25 | 3.9352 |
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+ | 3.987 | 4.96 | 31 | 3.8033 |
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+ | 3.8247 | 5.92 | 37 | 3.6821 |
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+ | 3.7534 | 6.88 | 43 | 3.5636 |
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+ | 3.067 | 8.0 | 50 | 3.4520 |
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+ | 3.4842 | 8.96 | 56 | 3.3944 |
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+ | 3.0348 | 9.6 | 60 | 3.3791 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ "loftq_config": {},
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+ "megatron_core": "megatron.core",
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+ "peft_type": "LORA",
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+ "r": 8,
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+ "rank_pattern": {},
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+ "target_modules": [
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+ "q_proj"
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+ ],
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+ "task_type": "CAUSAL_LM",
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+ "use_dora": false,
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+ "use_rslora": false
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+ }
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