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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: microsoft/Phi-3-mini-4k-instruct
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+ tags:
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+ - alignment-handbook
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+ - generated_from_trainer
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+ datasets:
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+ - trl-lib/kto-mix-14k
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+ - chaoweihuang/lf-response-phi3-f1_100_0.7-fg0.5
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+ model-index:
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+ - name: kto-mix-14k-lf-response-phi3-f1_100_0.7-fg0.5-kto-fg-fgudw4.0
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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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+ # kto-mix-14k-lf-response-phi3-f1_100_0.7-fg0.5-kto-fg-fgudw4.0
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+
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+ This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the trl-lib/kto-mix-14k and the chaoweihuang/lf-response-phi3-f1_100_0.7-fg0.5 datasets.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4815
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+ - Rewards/chosen: -0.6601
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+ - Logps/chosen: -299.7121
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+ - Rewards/rejected: -2.6435
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+ - Logps/rejected: -364.3744
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+ - Rewards/margins: 1.9834
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+ - Kl: 0.0081
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+ - Fg Kl: nan
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+ - Fg Rewards/chosen Sum: 0.0694
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+ - Fg Logps/policy Chosen: -15.2781
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+ - Fg Logps/reference Chosen: -14.9295
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+ - Count/fg Chosen: 16.0137
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+ - Fg Rewards/rejected Sum: -0.3623
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+ - Fg Logps/policy Rejected: -19.6552
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+ - Fg Logps/reference Rejected: -18.7868
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+ - Count/fg Rejected: 4.0824
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+ - Fg Logps/policy Kl: -21.1260
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+ - Fg Logps/reference Kl: -20.2070
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+ - Fg Loss: 0.7365
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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: 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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+ - num_devices: 2
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 16
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+ - total_eval_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: 1.0
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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 | Rewards/chosen | Logps/chosen | Rewards/rejected | Logps/rejected | Rewards/margins | Kl | Fg Kl | Fg Rewards/chosen Sum | Fg Logps/policy Chosen | Fg Logps/reference Chosen | Count/fg Chosen | Fg Rewards/rejected Sum | Fg Logps/policy Rejected | Fg Logps/reference Rejected | Count/fg Rejected | Fg Logps/policy Kl | Fg Logps/reference Kl | Fg Loss |
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+ |:-------------:|:------:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:--------------:|:---------------:|:------:|:-----:|:---------------------:|:----------------------:|:-------------------------:|:---------------:|:-----------------------:|:------------------------:|:---------------------------:|:-----------------:|:------------------:|:---------------------:|:-------:|
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+ | 0.4495 | 0.4103 | 400 | 0.4978 | -1.0397 | -303.5076 | -2.7182 | -365.1212 | 1.6785 | 0.0054 | nan | -1.3184 | -16.1070 | -14.9295 | 16.0137 | -0.5732 | -20.2671 | -18.7868 | 4.0824 | -21.1826 | -20.2070 | 0.7449 |
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+ | 0.5189 | 0.8206 | 800 | 0.4815 | -0.6601 | -299.7121 | -2.6435 | -364.3744 | 1.9834 | 0.0081 | nan | 0.0694 | -15.2781 | -14.9295 | 16.0137 | -0.3623 | -19.6552 | -18.7868 | 4.0824 | -21.1260 | -20.2070 | 0.7365 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.1
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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+ "train_samples_per_second": 1.144,
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+ "train_steps_per_second": 0.071
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+ }
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