End of training
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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: google-bert/bert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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- name: Randomized_Bert_Stacked_model_40
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results: []
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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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# Randomized_Bert_Stacked_model_40
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1549
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- F1: 0.5395
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 1.2617 | 1.0 | 631 | 1.1909 | 0.5071 |
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| 1.2223 | 2.0 | 1262 | 1.1752 | 0.5191 |
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| 1.1924 | 3.0 | 1893 | 1.1591 | 0.5334 |
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| 1.1486 | 4.0 | 2524 | 1.1545 | 0.5356 |
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| 1.1287 | 5.0 | 3155 | 1.1549 | 0.5395 |
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.5.0+cu121
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- Datasets 3.0.2
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- Tokenizers 0.19.1
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model.safetensors
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