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reversemult_lr5e-4_batch128_train1-5_eval6

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Safetensors
nanogpt
Generated from Trainer
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  1. README.md +216 -0
  2. config.json +19 -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: reversemult_lr5e-4_batch128_train1-5_eval6
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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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+ # reversemult_lr5e-4_batch128_train1-5_eval6
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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: 1.3785
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+ - Accuracy: 0.0057
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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: 0.0005
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+ - train_batch_size: 128
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+ - eval_batch_size: 512
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+ - seed: 23452399
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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 | 2.7162 | 0.0 |
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+ | 2.0296 | 0.0064 | 100 | 2.2743 | 0.0 |
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+ | 1.9424 | 0.0128 | 200 | 2.1654 | 0.0 |
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+ | 1.8836 | 0.0192 | 300 | 2.1261 | 0.0 |
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+ | 1.9049 | 0.0256 | 400 | 2.1056 | 0.0 |
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+ | 1.9108 | 0.032 | 500 | 2.1286 | 0.0 |
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+ | 1.7908 | 0.0384 | 600 | 2.0182 | 0.0 |
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+ | 1.6969 | 0.0448 | 700 | 1.9827 | 0.0 |
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+ | 1.6781 | 0.0512 | 800 | 1.9602 | 0.0 |
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+ | 1.575 | 0.0576 | 900 | 1.8370 | 0.0 |
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+ | 1.5587 | 0.064 | 1000 | 1.8525 | 0.0 |
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+ | 1.4983 | 0.0704 | 1100 | 1.9120 | 0.0 |
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+ | 1.5011 | 0.0768 | 1200 | 1.8729 | 0.0 |
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+ | 1.3519 | 0.0832 | 1300 | 1.8656 | 0.0 |
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+ | 1.4149 | 0.0896 | 1400 | 1.8366 | 0.0 |
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+ | 1.3179 | 0.096 | 1500 | 1.8383 | 0.0 |
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+ | 1.3261 | 0.1024 | 1600 | 1.7095 | 0.0 |
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+ | 1.4272 | 0.1088 | 1700 | 1.7269 | 0.0 |
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+ | 1.3181 | 0.1152 | 1800 | 1.8021 | 0.0 |
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+ | 1.3017 | 0.1216 | 1900 | 1.6781 | 0.0 |
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+ | 1.2954 | 0.128 | 2000 | 1.7248 | 0.0001 |
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+ | 1.3762 | 0.1344 | 2100 | 2.1858 | 0.0 |
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+ | 1.2999 | 0.1408 | 2200 | 1.6783 | 0.0 |
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+ | 1.2738 | 0.1472 | 2300 | 1.6780 | 0.0 |
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+ | 1.2304 | 0.1536 | 2400 | 1.7079 | 0.0 |
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+ | 1.2072 | 0.16 | 2500 | 1.6358 | 0.0001 |
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+ | 1.2027 | 0.1664 | 2600 | 1.6389 | 0.0001 |
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+ | 1.1565 | 0.1728 | 2700 | 1.7008 | 0.0 |
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+ | 1.1693 | 0.1792 | 2800 | 1.5942 | 0.0 |
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+ | 1.2066 | 0.1856 | 2900 | 1.6068 | 0.0001 |
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+ | 1.2295 | 0.192 | 3000 | 1.6025 | 0.0 |
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+ | 1.0896 | 0.1984 | 3100 | 1.7089 | 0.0 |
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+ | 1.1147 | 0.2048 | 3200 | 1.5786 | 0.0 |
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+ | 1.1365 | 0.2112 | 3300 | 1.5354 | 0.0001 |
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+ | 1.1456 | 0.2176 | 3400 | 1.5794 | 0.0001 |
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+ | 1.1195 | 0.224 | 3500 | 1.5774 | 0.0003 |
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+ | 1.1497 | 0.2304 | 3600 | 1.5569 | 0.0002 |
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+ | 1.1463 | 0.2368 | 3700 | 1.6149 | 0.0002 |
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+ | 1.1166 | 0.2432 | 3800 | 1.5591 | 0.0003 |
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+ | 1.1374 | 0.2496 | 3900 | 1.5637 | 0.0 |
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+ | 1.0243 | 0.256 | 4000 | 1.5328 | 0.0001 |
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+ | 1.0935 | 0.2624 | 4100 | 1.5287 | 0.0003 |
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+ | 1.0762 | 0.2688 | 4200 | 1.6777 | 0.0 |
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+ | 1.0035 | 0.2752 | 4300 | 1.5196 | 0.0 |
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+ | 1.0817 | 0.2816 | 4400 | 1.4903 | 0.0004 |
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+ | 1.0418 | 0.288 | 4500 | 1.5294 | 0.0004 |
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+ | 1.0771 | 0.2944 | 4600 | 1.5187 | 0.0 |
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+ | 1.0407 | 0.3008 | 4700 | 1.4713 | 0.0003 |
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+ | 0.9874 | 0.3072 | 4800 | 1.5375 | 0.0002 |
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+ | 0.9553 | 0.3136 | 4900 | 1.4886 | 0.0 |
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+ | 1.0734 | 0.32 | 5000 | 1.5172 | 0.0001 |
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+ | 1.012 | 0.3264 | 5100 | 1.8822 | 0.0002 |
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+ | 1.0574 | 0.3328 | 5200 | 1.5566 | 0.0003 |
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+ | 0.9948 | 0.3392 | 5300 | 1.5942 | 0.0001 |
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+ | 0.9474 | 0.3456 | 5400 | 1.5320 | 0.0004 |
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+ | 1.0058 | 0.352 | 5500 | 1.4921 | 0.0002 |
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+ | 1.0294 | 0.3584 | 5600 | 1.4531 | 0.0003 |
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+ | 0.994 | 0.3648 | 5700 | 1.4253 | 0.0005 |
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+ | 0.948 | 0.3712 | 5800 | 1.4519 | 0.0003 |
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+ | 0.9582 | 0.3776 | 5900 | 1.5040 | 0.0001 |
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+ | 0.9616 | 0.384 | 6000 | 1.5861 | 0.0003 |
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+ | 0.9159 | 0.3904 | 6100 | 1.5357 | 0.0001 |
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+ | 1.3541 | 0.3968 | 6200 | 2.4432 | 0.0003 |
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+ | 0.9235 | 0.4032 | 6300 | 1.4219 | 0.0001 |
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+ | 0.9238 | 0.4096 | 6400 | 1.4808 | 0.0002 |
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+ | 0.9173 | 0.416 | 6500 | 1.4324 | 0.0002 |
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+ | 0.9676 | 0.4224 | 6600 | 1.4826 | 0.0006 |
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+ | 0.9566 | 0.4288 | 6700 | 1.4554 | 0.0006 |
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+ | 0.8629 | 0.4416 | 6900 | 1.4216 | 0.0008 |
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+ | 0.9797 | 0.448 | 7000 | 1.4925 | 0.0003 |
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+ | 0.8934 | 0.4544 | 7100 | 1.4106 | 0.0002 |
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+ | 0.8281 | 0.4608 | 7200 | 1.4818 | 0.0005 |
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+ | 0.8121 | 0.4672 | 7300 | 1.4050 | 0.0003 |
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+ | 0.918 | 0.4736 | 7400 | 1.4581 | 0.0001 |
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+ | 0.9041 | 0.4864 | 7600 | 1.4066 | 0.0009 |
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+ | 0.9103 | 0.4928 | 7700 | 1.5262 | 0.0003 |
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+ | 0.8123 | 0.6528 | 10200 | 1.6016 | 0.0023 |
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+ | 0.7529 | 0.9984 | 15600 | 1.3785 | 0.0057 |
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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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+ "mlp_dim": 4,
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+ "model_type": "nanogpt",
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+ "n_embd": 384,
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+ "n_head": 6,
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+ "n_layer": 6,
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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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