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--- |
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library_name: transformers |
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language: |
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- en |
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base_model: gokulsrinivasagan/bert_base_lda_100_v1 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: bert_base_lda_100_v1_mrpc |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: GLUE MRPC |
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type: glue |
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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.6911764705882353 |
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- name: F1 |
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type: f1 |
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value: 0.8061538461538462 |
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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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# bert_base_lda_100_v1_mrpc |
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This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5799 |
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- Accuracy: 0.6912 |
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- F1: 0.8062 |
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- Combined Score: 0.7487 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
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| 0.6665 | 1.0 | 15 | 0.6144 | 0.6667 | 0.7606 | 0.7136 | |
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| 0.594 | 2.0 | 30 | 0.5915 | 0.7059 | 0.7952 | 0.7506 | |
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| 0.575 | 3.0 | 45 | 0.5799 | 0.6912 | 0.8062 | 0.7487 | |
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| 0.5285 | 4.0 | 60 | 0.5993 | 0.7034 | 0.7987 | 0.7511 | |
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| 0.4277 | 5.0 | 75 | 0.6557 | 0.6765 | 0.7537 | 0.7151 | |
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| 0.3244 | 6.0 | 90 | 0.8220 | 0.6961 | 0.8025 | 0.7493 | |
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| 0.2387 | 7.0 | 105 | 0.8552 | 0.6422 | 0.7256 | 0.6839 | |
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| 0.1466 | 8.0 | 120 | 1.0601 | 0.6691 | 0.7700 | 0.7196 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.20.3 |
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