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reverse_add_replicate_eval17_SGD

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Safetensors
nanogpt
Generated from Trainer
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  1. README.md +219 -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_SGD
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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_SGD
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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: 2.2622
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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: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 128
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+ - optimizer: Use OptimizerNames.SGD and the args are:
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+ 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 | 2.7691 | 0.0 |
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+ | 5.4494 | 0.0064 | 100 | 2.7152 | 0.0 |
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+ | 5.1839 | 0.0128 | 200 | 2.5964 | 0.0 |
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+ | 5.0056 | 0.0192 | 300 | 2.4931 | 0.0 |
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+ | 4.885 | 0.0256 | 400 | 2.4403 | 0.0 |
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+ | 4.8339 | 0.032 | 500 | 2.4154 | 0.0 |
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+ | 4.7944 | 0.0384 | 600 | 2.4005 | 0.0 |
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+ | 4.7774 | 0.0448 | 700 | 2.3900 | 0.0 |
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+ | 4.7665 | 0.0512 | 800 | 2.3820 | 0.0 |
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+ | 4.7421 | 0.0576 | 900 | 2.3750 | 0.0 |
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+ | 4.7048 | 0.064 | 1000 | 2.3691 | 0.0 |
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+ | 4.697 | 0.0704 | 1100 | 2.3660 | 0.0 |
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+ | 4.6785 | 0.0768 | 1200 | 2.3630 | 0.0 |
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+ | 4.6977 | 0.0832 | 1300 | 2.3622 | 0.0 |
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+ | 4.6974 | 0.0896 | 1400 | 2.3597 | 0.0 |
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+ | 4.6926 | 0.096 | 1500 | 2.3576 | 0.0 |
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+ | 4.6554 | 0.1024 | 1600 | 2.3567 | 0.0 |
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+ | 4.6593 | 0.1088 | 1700 | 2.3558 | 0.0 |
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+ | 4.6801 | 0.1152 | 1800 | 2.3531 | 0.0 |
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+ | 4.6731 | 0.1216 | 1900 | 2.3548 | 0.0 |
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+ | 4.6353 | 0.128 | 2000 | 2.3534 | 0.0 |
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+ | 4.6868 | 0.1344 | 2100 | 2.3495 | 0.0 |
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+ | 4.6249 | 0.1408 | 2200 | 2.3482 | 0.0 |
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+ | 4.6446 | 0.1472 | 2300 | 2.3489 | 0.0 |
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+ | 4.6306 | 0.1536 | 2400 | 2.3479 | 0.0 |
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+ | 4.6054 | 0.16 | 2500 | 2.3452 | 0.0 |
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+ | 4.624 | 0.1664 | 2600 | 2.3504 | 0.0 |
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+ | 4.5921 | 0.1728 | 2700 | 2.3329 | 0.0 |
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+ | 4.6153 | 0.1792 | 2800 | 2.3307 | 0.0 |
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+ | 4.6157 | 0.1856 | 2900 | 2.3416 | 0.0 |
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+ | 4.5645 | 0.192 | 3000 | 2.3227 | 0.0 |
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+ | 4.6075 | 0.1984 | 3100 | 2.3395 | 0.0 |
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+ | 4.5375 | 0.2048 | 3200 | 2.3418 | 0.0 |
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+ | 4.6178 | 0.2112 | 3300 | 2.3424 | 0.0 |
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+ | 4.5336 | 0.2304 | 3600 | 2.3375 | 0.0 |
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+ | 4.5392 | 0.256 | 4000 | 2.3337 | 0.0 |
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+ | 4.4875 | 0.2688 | 4200 | 2.3290 | 0.0 |
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+ | 4.4972 | 0.2752 | 4300 | 2.3291 | 0.0 |
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+ | 4.5155 | 0.2816 | 4400 | 2.3300 | 0.0 |
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+ | 4.5351 | 0.288 | 4500 | 2.3318 | 0.0 |
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+ | 4.4892 | 0.2944 | 4600 | 2.3293 | 0.0 |
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+ | 4.4802 | 0.3008 | 4700 | 2.3254 | 0.0 |
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+ | 4.4911 | 0.3136 | 4900 | 2.3251 | 0.0 |
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+ | 4.4039 | 0.9984 | 15600 | 2.2622 | 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": 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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