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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: Hartunka/bert_base_rand_50_v2 |
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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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- spearmanr |
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model-index: |
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- name: bert_base_rand_50_v2_stsb |
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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 STSB |
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type: glue |
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args: stsb |
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metrics: |
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- name: Spearmanr |
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type: spearmanr |
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value: 0.2921098166729177 |
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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_rand_50_v2_stsb |
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This model is a fine-tuned version of [Hartunka/bert_base_rand_50_v2](https://huggingface.co/Hartunka/bert_base_rand_50_v2) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1775 |
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- Pearson: 0.3055 |
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- Spearmanr: 0.2921 |
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- Combined Score: 0.2988 |
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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 | Pearson | Spearmanr | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
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| 2.7742 | 1.0 | 23 | 2.6998 | 0.1242 | 0.1041 | 0.1142 | |
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| 1.9014 | 2.0 | 46 | 2.2005 | 0.2317 | 0.2121 | 0.2219 | |
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| 1.647 | 3.0 | 69 | 2.1775 | 0.3055 | 0.2921 | 0.2988 | |
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| 1.2684 | 4.0 | 92 | 2.2438 | 0.3100 | 0.2998 | 0.3049 | |
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| 0.9726 | 5.0 | 115 | 2.6894 | 0.2978 | 0.2932 | 0.2955 | |
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| 0.7533 | 6.0 | 138 | 2.5985 | 0.3103 | 0.3100 | 0.3101 | |
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| 0.5559 | 7.0 | 161 | 2.5141 | 0.3397 | 0.3405 | 0.3401 | |
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| 0.4489 | 8.0 | 184 | 2.7038 | 0.3280 | 0.3296 | 0.3288 | |
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### Framework versions |
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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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