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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-v4
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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-v4
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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: 1.9080
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+ - Rewards/chosen: -0.6019
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+ - Rewards/rejected: -0.7507
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+ - Rewards/accuracies: 0.6259
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+ - Rewards/margins: 0.1488
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+ - Logps/rejected: -1.5015
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+ - Logps/chosen: -1.2038
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+ - Logits/rejected: 247.6263
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+ - Logits/chosen: 282.0085
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+ - Nll Loss: 1.5545
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+ - Log Odds Ratio: -0.6477
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+ - Log Odds Chosen: 0.4230
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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-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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+ | 1.8238 | 0.9955 | 167 | 1.8176 | -0.5378 | -0.6319 | 0.5468 | 0.0941 | -1.2637 | -1.0755 | 293.2744 | 322.6454 | 1.4783 | -0.6631 | 0.2616 |
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+ | 1.3092 | 1.9970 | 335 | 1.7560 | -0.5202 | -0.6309 | 0.5324 | 0.1106 | -1.2617 | -1.0405 | 279.0659 | 309.3900 | 1.4054 | -0.6637 | 0.3224 |
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+ | 0.6827 | 2.9866 | 501 | 1.9080 | -0.6019 | -0.7507 | 0.6259 | 0.1488 | -1.5015 | -1.2038 | 247.6263 | 282.0085 | 1.5545 | -0.6477 | 0.4230 |
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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 2.4.1+cu121
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+ - Datasets 3.0.0
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+ - Tokenizers 0.19.1
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+ "train_samples": 5364,
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+ "train_samples_per_second": 0.509,
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+ "train_steps_per_second": 0.016
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+ }
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+ "transformers_version": "4.44.2",
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+ "use_cache": false,
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+ "vocab_size": 256000
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+ }
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