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mtzig
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reverse_add_replicate_eval17_small_1layer

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Safetensors
nanogpt
Generated from Trainer
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  1. README.md +216 -0
  2. config.json +18 -0
  3. generation_config.json +4 -0
  4. model.safetensors +3 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: reverse_add_replicate_eval17_small_1layer
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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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+ # reverse_add_replicate_eval17_small_1layer
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.3913
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+ - Accuracy: 0.0
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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: 0.001
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 7658372
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 | Accuracy |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | No log | 0 | 0 | 2.6439 | 0.0 |
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+ | 2.6225 | 0.0064 | 100 | 2.6206 | 0.0 |
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+ | 2.5747 | 0.0128 | 200 | 2.5737 | 0.0 |
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+ | 2.532 | 0.0192 | 300 | 2.5299 | 0.0 |
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+ | 2.4906 | 0.0256 | 400 | 2.4887 | 0.0 |
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+ | 2.458 | 0.032 | 500 | 2.4563 | 0.0 |
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+ | 2.4362 | 0.0384 | 600 | 2.4341 | 0.0 |
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+ | 2.4228 | 0.0448 | 700 | 2.4199 | 0.0 |
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+ | 2.4101 | 0.0512 | 800 | 2.4106 | 0.0 |
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+ | 2.3985 | 0.0576 | 900 | 2.4019 | 0.0 |
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+ | 2.3933 | 0.064 | 1000 | 2.3970 | 0.0 |
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+ | 2.3863 | 0.0704 | 1100 | 2.4012 | 0.0 |
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+ | 2.3755 | 0.0768 | 1200 | 2.4138 | 0.0 |
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+ | 2.3761 | 0.0832 | 1300 | 2.3951 | 0.0 |
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+ | 2.3719 | 0.0896 | 1400 | 2.3799 | 0.0 |
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+ | 2.3739 | 0.096 | 1500 | 2.3844 | 0.0 |
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+ | 2.3714 | 0.1024 | 1600 | 2.3876 | 0.0 |
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+ | 2.3671 | 0.1088 | 1700 | 2.3918 | 0.0 |
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+ | 2.3652 | 0.1152 | 1800 | 2.3910 | 0.0 |
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+ | 2.3665 | 0.1216 | 1900 | 2.3939 | 0.0 |
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+ | 2.3671 | 0.128 | 2000 | 2.4437 | 0.0 |
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+ | 2.3652 | 0.1344 | 2100 | 2.3865 | 0.0 |
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+ | 2.3597 | 0.1408 | 2200 | 2.4123 | 0.0 |
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+ | 2.3642 | 0.1472 | 2300 | 2.3968 | 0.0 |
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+ | 2.3744 | 0.1536 | 2400 | 2.3691 | 0.0 |
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+ | 2.3699 | 0.16 | 2500 | 2.3906 | 0.0 |
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+ | 2.3652 | 0.1664 | 2600 | 2.3917 | 0.0 |
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+ | 2.365 | 0.1728 | 2700 | 2.3736 | 0.0 |
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+ | 2.3601 | 0.1792 | 2800 | 2.3954 | 0.0 |
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+ | 2.3617 | 0.1856 | 2900 | 2.4001 | 0.0 |
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+ | 2.3626 | 0.192 | 3000 | 2.3838 | 0.0 |
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+ | 2.3629 | 0.1984 | 3100 | 2.4000 | 0.0 |
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+ | 2.3747 | 0.2048 | 3200 | 2.3742 | 0.0 |
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+ | 2.3582 | 0.2112 | 3300 | 2.3776 | 0.0 |
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+ | 2.3633 | 0.2176 | 3400 | 2.3883 | 0.0 |
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+ | 2.3695 | 0.224 | 3500 | 2.3982 | 0.0 |
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+ | 2.3691 | 0.2304 | 3600 | 2.3675 | 0.0 |
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+ | 2.3554 | 0.2368 | 3700 | 2.3930 | 0.0 |
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+ | 2.3586 | 0.2432 | 3800 | 2.3859 | 0.0 |
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+ | 2.3683 | 0.2496 | 3900 | 2.4121 | 0.0 |
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+ | 2.3614 | 0.256 | 4000 | 2.3832 | 0.0 |
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+ | 2.3662 | 0.2624 | 4100 | 2.3990 | 0.0 |
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+ | 2.3669 | 0.2688 | 4200 | 2.3810 | 0.0 |
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+ | 2.3628 | 0.2752 | 4300 | 2.3730 | 0.0 |
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+ | 2.3619 | 0.2816 | 4400 | 2.3770 | 0.0 |
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+ | 2.3578 | 0.288 | 4500 | 2.4060 | 0.0 |
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+ | 2.3636 | 0.2944 | 4600 | 2.3799 | 0.0 |
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+ | 2.3542 | 0.3008 | 4700 | 2.3775 | 0.0 |
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+ | 2.358 | 0.3072 | 4800 | 2.3850 | 0.0 |
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+ | 2.3581 | 0.3136 | 4900 | 2.3708 | 0.0 |
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+ | 2.3649 | 0.32 | 5000 | 2.3891 | 0.0 |
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+ | 2.3557 | 0.3264 | 5100 | 2.3882 | 0.0 |
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+ | 2.3605 | 0.3328 | 5200 | 2.3921 | 0.0 |
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+ | 2.36 | 0.3392 | 5300 | 2.3658 | 0.0 |
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+ | 2.3586 | 0.3456 | 5400 | 2.3626 | 0.0 |
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+ | 2.3622 | 0.352 | 5500 | 2.3836 | 0.0 |
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+ | 2.3602 | 0.3584 | 5600 | 2.3953 | 0.0 |
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+ | 2.3598 | 0.3648 | 5700 | 2.3848 | 0.0 |
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+ | 2.3687 | 0.3712 | 5800 | 2.3791 | 0.0 |
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+ | 2.3632 | 0.3776 | 5900 | 2.3883 | 0.0 |
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+ | 2.3621 | 0.384 | 6000 | 2.3718 | 0.0 |
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+ | 2.3532 | 0.3904 | 6100 | 2.3732 | 0.0 |
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+ | 2.3594 | 0.3968 | 6200 | 2.3984 | 0.0 |
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+ | 2.357 | 0.4032 | 6300 | 2.3686 | 0.0 |
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+ | 2.3685 | 0.4096 | 6400 | 2.3903 | 0.0 |
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+ | 2.366 | 0.6336 | 9900 | 2.3719 | 0.0 |
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+ | 2.3589 | 0.64 | 10000 | 2.3942 | 0.0 |
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+ | 2.3563 | 0.6464 | 10100 | 2.4036 | 0.0 |
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+ | 2.361 | 0.6528 | 10200 | 2.4062 | 0.0 |
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+ | 2.3515 | 0.7936 | 12400 | 2.3866 | 0.0 |
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+ | 2.351 | 0.8 | 12500 | 2.3947 | 0.0 |
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+ | 2.3645 | 0.8128 | 12700 | 2.3987 | 0.0 |
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+ | 2.3584 | 0.8192 | 12800 | 2.3957 | 0.0 |
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+ | 2.3568 | 0.8256 | 12900 | 2.3910 | 0.0 |
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+ | 2.3664 | 0.832 | 13000 | 2.3861 | 0.0 |
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+ | 2.3514 | 0.8512 | 13300 | 2.3950 | 0.0 |
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+ | 2.3636 | 0.8576 | 13400 | 2.3925 | 0.0 |
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+ | 2.3601 | 0.864 | 13500 | 2.3933 | 0.0 |
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+ | 2.3539 | 0.8704 | 13600 | 2.3955 | 0.0 |
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+ | 2.3632 | 0.8832 | 13800 | 2.3906 | 0.0 |
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+ | 2.3582 | 0.8896 | 13900 | 2.3925 | 0.0 |
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+ | 2.3599 | 0.896 | 14000 | 2.3853 | 0.0 |
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+ | 2.3652 | 0.9024 | 14100 | 2.3966 | 0.0 |
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+ | 2.362 | 0.9088 | 14200 | 2.3913 | 0.0 |
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+ | 2.3616 | 0.9344 | 14600 | 2.3926 | 0.0 |
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+ | 2.3642 | 0.9472 | 14800 | 2.3907 | 0.0 |
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+ | 2.3618 | 0.9856 | 15400 | 2.3913 | 0.0 |
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+ | 2.3604 | 0.992 | 15500 | 2.3913 | 0.0 |
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+ | 2.3583 | 0.9984 | 15600 | 2.3913 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.0
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+ - Pytorch 2.5.1
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.1
config.json ADDED
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+ {
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+ "architectures": [
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+ "NanoGPT"
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+ ],
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+ "bias": true,
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+ "block_size": 256,
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+ "dropout": 0.0,
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+ "model_type": "nanogpt",
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+ "n_embd": 8,
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+ "n_head": 1,
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+ "n_layer": 1,
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+ "nonlinearity": "RELU",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.46.0",
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+ "use_NoPE": true,
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+ "use_layernorm": true,
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+ "vocab_size": 14
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+ }
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "transformers_version": "4.46.0"
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+ }
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