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README.md ADDED
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+ ---
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+ library_name: transformers
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+ base_model: Hartunka/bert_base_rand_100_v1
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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: bert_base_rand_100_v1_wnli
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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_base_rand_100_v1_wnli
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+
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+ This model is a fine-tuned version of [Hartunka/bert_base_rand_100_v1](https://huggingface.co/Hartunka/bert_base_rand_100_v1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8210
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+ - Accuracy: 0.1972
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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: 256
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+ - eval_batch_size: 256
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+ - seed: 10
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+ - optimizer: Use 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 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6987 | 1.0 | 3 | 0.7065 | 0.2958 |
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+ | 0.6957 | 2.0 | 6 | 0.7060 | 0.5070 |
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+ | 0.694 | 3.0 | 9 | 0.7249 | 0.3099 |
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+ | 0.6932 | 4.0 | 12 | 0.7266 | 0.4085 |
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+ | 0.693 | 5.0 | 15 | 0.7479 | 0.2254 |
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+ | 0.6904 | 6.0 | 18 | 0.7845 | 0.2535 |
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+ | 0.6908 | 7.0 | 21 | 0.8210 | 0.1972 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.50.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.21.1
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