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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: llama3.2
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+ base_model: tanliboy/llama-3.2-3b-sft
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+ tags:
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+ - trl
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+ - dpo
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+ - generated_from_trainer
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+ model-index:
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+ - name: llama-3.2-3b-dpo
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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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+ # llama-3.2-3b-dpo
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+
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+ This model is a fine-tuned version of [tanliboy/llama-3.2-3b-sft](https://huggingface.co/tanliboy/llama-3.2-3b-sft) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4864
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+ - Rewards/chosen: -1.4549
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+ - Rewards/rejected: -2.6071
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+ - Rewards/accuracies: 0.7247
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+ - Rewards/margins: 1.1522
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+ - Logps/rejected: -560.2480
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+ - Logps/chosen: -483.4225
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+ - Logits/rejected: 0.5181
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+ - Logits/chosen: 0.3637
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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: 5e-07
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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: 8
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 32
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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: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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+ |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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+ | 0.6115 | 0.1741 | 100 | 0.6000 | -0.3357 | -0.5534 | 0.6329 | 0.2176 | -354.8722 | -371.5030 | 0.8149 | 0.6445 |
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+ | 0.5416 | 0.3483 | 200 | 0.5221 | -1.2141 | -1.9406 | 0.6741 | 0.7265 | -493.5951 | -459.3420 | 0.6298 | 0.4810 |
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+ | 0.5158 | 0.5224 | 300 | 0.5048 | -1.3617 | -2.3705 | 0.7057 | 1.0088 | -536.5855 | -474.1037 | 0.4784 | 0.3320 |
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+ | 0.501 | 0.6966 | 400 | 0.4906 | -1.4306 | -2.5214 | 0.7152 | 1.0908 | -551.6774 | -480.9883 | 0.5108 | 0.3615 |
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+ | 0.4806 | 0.8707 | 500 | 0.4864 | -1.4549 | -2.6071 | 0.7247 | 1.1522 | -560.2480 | -483.4225 | 0.5181 | 0.3637 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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+ "train_runtime": 4250.8819,
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+ "train_samples": 73493,
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+ "train_samples_per_second": 17.289,
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+ "train_steps_per_second": 0.135
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+ }
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