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Model save

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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: gemma
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+ base_model: google/gemma-7b
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+ tags:
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+ - trl
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+ - orpo
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+ - generated_from_trainer
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+ model-index:
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+ - name: gemma-7b-borpo-low-quality-v5
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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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+ # gemma-7b-borpo-low-quality-v5
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+
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+ This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.0035
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+ - Rewards/chosen: -0.6455
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+ - Rewards/rejected: -0.7620
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+ - Rewards/accuracies: 0.6115
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+ - Rewards/margins: 0.1164
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+ - Logps/rejected: -1.5240
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+ - Logps/chosen: -1.2911
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+ - Logits/rejected: 259.2041
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+ - Logits/chosen: 292.7468
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+ - Nll Loss: 1.6440
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+ - Log Odds Ratio: -0.6769
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+ - Log Odds Chosen: 0.3357
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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: 7.5e-06
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+ - train_batch_size: 2
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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: 4
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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+ - total_eval_batch_size: 4
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: inverse_sqrt
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 3
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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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
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+ |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
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+ | 1.8398 | 0.9955 | 167 | 1.8982 | -0.5762 | -0.6715 | 0.5180 | 0.0953 | -1.3431 | -1.1525 | 302.9095 | 331.1552 | 1.5454 | -0.6749 | 0.2542 |
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+ | 1.299 | 1.9970 | 335 | 1.8186 | -0.5507 | -0.6510 | 0.5396 | 0.1003 | -1.3021 | -1.1014 | 282.3183 | 313.4974 | 1.4682 | -0.6666 | 0.3074 |
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+ | 0.6379 | 2.9866 | 501 | 2.0035 | -0.6455 | -0.7620 | 0.6115 | 0.1164 | -1.5240 | -1.2911 | 259.2041 | 292.7468 | 1.6440 | -0.6769 | 0.3357 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.1
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.0
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+ "train_samples_per_second": 0.479,
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+ "train_steps_per_second": 0.015
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+ }
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+ "vocab_size": 256000
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