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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: nreimers/BERT-Tiny_L-2_H-128_A-2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bert_tiny_trained
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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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+ # bert_tiny_trained
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+
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+ This model is a fine-tuned version of [nreimers/BERT-Tiny_L-2_H-128_A-2](https://huggingface.co/nreimers/BERT-Tiny_L-2_H-128_A-2) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8101
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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-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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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: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 2 | 1.0244 |
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+ | No log | 2.0 | 4 | 1.0190 |
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+ | No log | 3.0 | 6 | 1.0148 |
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+ | No log | 4.0 | 8 | 1.0122 |
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+ | No log | 5.0 | 10 | 1.0101 |
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+ | No log | 6.0 | 12 | 1.0061 |
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+ | No log | 7.0 | 14 | 1.0020 |
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+ | No log | 8.0 | 16 | 0.9957 |
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+ | No log | 9.0 | 18 | 0.9890 |
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+ | No log | 10.0 | 20 | 0.9804 |
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+ | No log | 11.0 | 22 | 0.9692 |
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+ | No log | 12.0 | 24 | 0.9561 |
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+ | No log | 13.0 | 26 | 0.9443 |
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+ | No log | 14.0 | 28 | 0.9345 |
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+ | No log | 15.0 | 30 | 0.9262 |
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+ | No log | 16.0 | 32 | 0.9178 |
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+ | No log | 17.0 | 34 | 0.9089 |
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+ | No log | 18.0 | 36 | 0.9011 |
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+ | No log | 19.0 | 38 | 0.8937 |
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+ | No log | 20.0 | 40 | 0.8868 |
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+ | No log | 21.0 | 42 | 0.8807 |
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+ | No log | 22.0 | 44 | 0.8757 |
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+ | No log | 23.0 | 46 | 0.8714 |
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+ | No log | 24.0 | 48 | 0.8671 |
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+ | No log | 25.0 | 50 | 0.8626 |
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+ | No log | 26.0 | 52 | 0.8581 |
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+ | No log | 27.0 | 54 | 0.8537 |
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+ | No log | 28.0 | 56 | 0.8499 |
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+ | No log | 29.0 | 58 | 0.8457 |
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+ | No log | 30.0 | 60 | 0.8423 |
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+ | No log | 31.0 | 62 | 0.8395 |
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+ | No log | 32.0 | 64 | 0.8364 |
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+ | No log | 33.0 | 66 | 0.8334 |
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+ | No log | 34.0 | 68 | 0.8307 |
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+ | No log | 35.0 | 70 | 0.8281 |
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+ | No log | 36.0 | 72 | 0.8259 |
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+ | No log | 37.0 | 74 | 0.8238 |
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+ | No log | 38.0 | 76 | 0.8223 |
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+ | No log | 39.0 | 78 | 0.8206 |
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+ | No log | 40.0 | 80 | 0.8192 |
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+ | No log | 41.0 | 82 | 0.8181 |
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+ | No log | 42.0 | 84 | 0.8170 |
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+ | No log | 43.0 | 86 | 0.8159 |
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+ | No log | 44.0 | 88 | 0.8146 |
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+ | No log | 45.0 | 90 | 0.8134 |
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+ | No log | 46.0 | 92 | 0.8122 |
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+ | No log | 47.0 | 94 | 0.8115 |
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+ | No log | 48.0 | 96 | 0.8108 |
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+ | No log | 49.0 | 98 | 0.8102 |
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+ | No log | 50.0 | 100 | 0.8101 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.0
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "type_vocab_size": 2,
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