Hemanth-thunder commited on
Commit
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Hemanth-thunder/aimo-lora-deepseek-math

Browse files
README.md CHANGED
@@ -1,7 +1,7 @@
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  ---
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- base_model: microsoft/Phi-3-mini-128k-instruct
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  library_name: peft
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- license: mit
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  tags:
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  - trl
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  - sft
@@ -16,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # phi-3-mini-LoRA
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- This model is a fine-tuned version of [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3525
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  ## Model description
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@@ -39,36 +39,31 @@ More information needed
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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: 2
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  - seed: 42
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- - gradient_accumulation_steps: 2
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- - total_train_batch_size: 2
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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_ratio: 0.1
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- - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.3351 | 0.17 | 500 | 0.3755 |
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- | 0.3312 | 0.34 | 1000 | 0.3644 |
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- | 0.3079 | 0.51 | 1500 | 0.3597 |
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- | 0.3195 | 0.68 | 2000 | 0.3577 |
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- | 0.3218 | 0.85 | 2500 | 0.3557 |
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- | 0.3034 | 1.02 | 3000 | 0.3553 |
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- | 0.296 | 1.19 | 3500 | 0.3543 |
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- | 0.3175 | 1.36 | 4000 | 0.3539 |
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- | 0.3257 | 1.53 | 4500 | 0.3533 |
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- | 0.3263 | 1.7 | 5000 | 0.3526 |
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- | 0.3209 | 1.87 | 5500 | 0.3522 |
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- | 0.3221 | 2.04 | 6000 | 0.3528 |
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- | 0.2927 | 2.21 | 6500 | 0.3526 |
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- | 0.2922 | 2.38 | 7000 | 0.3527 |
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- | 0.2968 | 2.55 | 7500 | 0.3525 |
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- | 0.2968 | 2.72 | 8000 | 0.3526 |
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- | 0.3094 | 2.89 | 8500 | 0.3525 |
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  ### Framework versions
 
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  ---
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+ base_model: deepseek-ai/deepseek-math-7b-base
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  library_name: peft
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+ license: other
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  tags:
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  - trl
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  - sft
 
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  # phi-3-mini-LoRA
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+ This model is a fine-tuned version of [deepseek-ai/deepseek-math-7b-base](https://huggingface.co/deepseek-ai/deepseek-math-7b-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4014
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  ## Model description
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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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  - 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_ratio: 0.1
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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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+ | 0.4522 | 0.07 | 500 | 0.4533 |
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+ | 0.4512 | 0.14 | 1000 | 0.4301 |
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+ | 0.4386 | 0.21 | 1500 | 0.4199 |
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+ | 0.4268 | 0.28 | 2000 | 0.4144 |
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+ | 0.4167 | 0.35 | 2500 | 0.4104 |
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+ | 0.3955 | 0.42 | 3000 | 0.4092 |
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+ | 0.436 | 0.49 | 3500 | 0.4062 |
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+ | 0.3912 | 0.55 | 4000 | 0.4057 |
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+ | 0.425 | 0.62 | 4500 | 0.4036 |
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+ | 0.4066 | 0.69 | 5000 | 0.4026 |
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+ | 0.3963 | 0.76 | 5500 | 0.4016 |
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+ | 0.3862 | 0.83 | 6000 | 0.4019 |
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+ | 0.3902 | 0.9 | 6500 | 0.4015 |
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+ | 0.4364 | 0.97 | 7000 | 0.4014 |
 
 
 
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  ### Framework versions
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