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End of training

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  1. README.md +9 -12
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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [zake7749/gemma-2-2b-it-chinese-kyara-dpo](https://huggingface.co/zake7749/gemma-2-2b-it-chinese-kyara-dpo) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.7677
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  ## Model description
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@@ -35,7 +35,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -43,21 +43,18 @@ The following hyperparameters were used during training:
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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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- - num_epochs: 6
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 2.4381 | 0.64 | 200 | 2.2165 |
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- | 1.9414 | 1.28 | 400 | 2.3546 |
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- | 1.5135 | 1.92 | 600 | 2.3314 |
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- | 0.7845 | 2.56 | 800 | 2.8106 |
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- | 0.5724 | 3.2 | 1000 | 3.4573 |
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- | 0.2391 | 3.84 | 1200 | 3.4574 |
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- | 0.1169 | 4.48 | 1400 | 3.7176 |
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- | 0.0685 | 5.12 | 1600 | 3.7769 |
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- | 0.0195 | 5.76 | 1800 | 3.7677 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [zake7749/gemma-2-2b-it-chinese-kyara-dpo](https://huggingface.co/zake7749/gemma-2-2b-it-chinese-kyara-dpo) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.0069
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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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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+ - 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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+ | 2.3853 | 0.64 | 200 | 2.1371 |
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+ | 1.9709 | 1.28 | 400 | 2.1690 |
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+ | 1.6145 | 1.92 | 600 | 2.1344 |
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+ | 1.1069 | 2.56 | 800 | 2.4925 |
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+ | 0.849 | 3.2 | 1000 | 3.0008 |
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+ | 0.5224 | 3.84 | 1200 | 3.0069 |
 
 
 
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  ### Framework versions