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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: mistralai/Mixtral-8x7B-Instruct-v0.1
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: notux-8x7b-v1-alt
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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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+ # notux-8x7b-v1-alt
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+
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+ This model is a fine-tuned version of [mistralai/Mixtral-8x7B-Instruct-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4217
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+ - Rewards/chosen: -0.1933
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+ - Rewards/rejected: -2.2968
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+ - Rewards/accuracies: 0.8135
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+ - Rewards/margins: 2.1035
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+ - Logps/rejected: -409.3196
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+ - Logps/chosen: -396.5202
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+ - Logits/rejected: -1.2925
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+ - Logits/chosen: -1.2132
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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: 8
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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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+ - total_train_batch_size: 64
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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: linear
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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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+ | 0.4384 | 0.22 | 200 | 0.4556 | -0.3275 | -1.9448 | 0.7937 | 1.6174 | -405.7994 | -397.8617 | -1.3157 | -1.4511 |
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+ | 0.4064 | 0.43 | 400 | 0.4286 | -0.2163 | -2.2090 | 0.8254 | 1.9927 | -408.4409 | -396.7496 | -0.7660 | -0.6539 |
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+ | 0.3952 | 0.65 | 600 | 0.4275 | -0.1311 | -2.1603 | 0.8016 | 2.0291 | -407.9537 | -395.8982 | -0.6783 | -0.7206 |
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+ | 0.3909 | 0.87 | 800 | 0.4167 | -0.2273 | -2.3146 | 0.8135 | 2.0872 | -409.4968 | -396.8602 | -0.8458 | -0.7738 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.15.0
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+ "eval_loss": 0.4216844439506531,
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+ "eval_rewards/accuracies": 0.8134920597076416,
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+ "eval_rewards/chosen": -0.1933162659406662,
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+ "eval_rewards/margins": 2.1035311222076416,
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+ "eval_rewards/rejected": -2.296847343444824,
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+ "eval_runtime": 398.9749,
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+ "eval_samples": 2000,
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+ "eval_samples_per_second": 5.013,
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+ "eval_steps_per_second": 0.158,
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+ "train_loss": 0.4461688995361328,
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+ "train_runtime": 44067.2139,
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+ "train_samples": 58917,
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+ "train_samples_per_second": 1.337,
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+ "train_steps_per_second": 0.021
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+ }
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+ "vocab_size": 32000
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+ }
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+ "eval_rewards/margins": 2.1035311222076416,
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+ "eval_steps_per_second": 0.158
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