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HybridModelScratch

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hybrid_fourier_lm
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  1. README.md +84 -0
  2. best_model_streaming/config.json +31 -0
  3. best_model_streaming/model.safetensors +3 -0
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  9. tokenizer.json +0 -0
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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: HybridModelScratch
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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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+ # HybridModelScratch
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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: 6.0191
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+ - Accuracy: 0.1528
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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: 0.0001
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+ - train_batch_size: 64
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 2
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 1024
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+ - total_eval_batch_size: 32
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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_steps: 150
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+ - training_steps: 2000
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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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+ | 133.1257 | 0.05 | 100 | 7.7065 | 0.0876 |
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+ | 107.0186 | 0.1 | 200 | 6.6099 | 0.1364 |
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+ | 102.3462 | 0.15 | 300 | 6.3677 | 0.1448 |
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+ | 99.0524 | 0.2 | 400 | 6.2145 | 0.1531 |
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+ | 96.6031 | 0.25 | 500 | 6.1010 | 0.1584 |
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+ | 95.9314 | 0.3 | 600 | 5.9869 | 0.1640 |
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+ | 95.0101 | 0.35 | 700 | 5.8890 | 0.1683 |
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+ | 94.2643 | 0.4 | 800 | 5.8284 | 0.1715 |
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+ | 93.2266 | 0.45 | 900 | 5.7744 | 0.1746 |
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+ | 92.0125 | 0.5 | 1000 | 5.7337 | 0.1763 |
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+ | 95.8613 | 0.55 | 1100 | 6.0068 | 0.1554 |
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+ | 98.1012 | 0.6 | 1200 | 6.1055 | 0.1491 |
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+ | 97.152 | 0.65 | 1300 | 6.0546 | 0.1512 |
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+ | 97.8734 | 0.7 | 1400 | 6.0947 | 0.1474 |
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+ | 97.4964 | 0.75 | 1500 | 6.0419 | 0.1510 |
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+ | 97.562 | 0.8 | 1600 | 6.0272 | 0.1518 |
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+ | 97.3206 | 0.85 | 1700 | 6.0171 | 0.1529 |
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+ | 96.8684 | 0.9 | 1800 | 6.0163 | 0.1532 |
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+ | 96.472 | 0.95 | 1900 | 6.0193 | 0.1528 |
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+ | 96.5051 | 1.0 | 2000 | 6.0191 | 0.1528 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.56.0
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+ - Pytorch 2.8.0+cu129
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+ - Datasets 5.0.0
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+ - Tokenizers 0.22.0
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+ "normalized": true,
202
+ "rstrip": false,
203
+ "single_word": false,
204
+ "special": false
205
+ }
206
+ },
207
+ "bos_token": "<|endoftext|>",
208
+ "clean_up_tokenization_spaces": false,
209
+ "eos_token": "<|endoftext|>",
210
+ "extra_special_tokens": {},
211
+ "model_max_length": 1000000000,
212
+ "pad_token": "<|endoftext|>",
213
+ "tokenizer_class": "GPTNeoXTokenizer",
214
+ "unk_token": "<|endoftext|>"
215
+ }