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--- |
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language: |
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- en |
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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: hBERTv1_new_pretrain_w_init_48_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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config: stsb |
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split: validation |
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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: 0.7471924680940966 |
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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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# hBERTv1_new_pretrain_w_init_48_stsb |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9800 |
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- Pearson: 0.7515 |
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- Spearmanr: 0.7472 |
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- Combined Score: 0.7493 |
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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: 4e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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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: 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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| 2.5456 | 1.0 | 45 | 2.2706 | 0.1246 | 0.1141 | 0.1194 | |
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| 2.0514 | 2.0 | 90 | 2.0613 | 0.5266 | 0.5198 | 0.5232 | |
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| 1.3837 | 3.0 | 135 | 1.1984 | 0.6853 | 0.6942 | 0.6897 | |
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| 1.0297 | 4.0 | 180 | 1.6176 | 0.6869 | 0.6961 | 0.6915 | |
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| 0.8064 | 5.0 | 225 | 1.1444 | 0.7476 | 0.7445 | 0.7460 | |
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| 0.604 | 6.0 | 270 | 1.2754 | 0.7422 | 0.7450 | 0.7436 | |
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| 0.4818 | 7.0 | 315 | 1.1407 | 0.7687 | 0.7673 | 0.7680 | |
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| 0.3905 | 8.0 | 360 | 1.1860 | 0.7560 | 0.7604 | 0.7582 | |
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| 0.3476 | 9.0 | 405 | 0.9800 | 0.7515 | 0.7472 | 0.7493 | |
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| 0.2819 | 10.0 | 450 | 1.0156 | 0.7521 | 0.7507 | 0.7514 | |
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| 0.2418 | 11.0 | 495 | 1.0174 | 0.7516 | 0.7480 | 0.7498 | |
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| 0.2068 | 12.0 | 540 | 1.2367 | 0.7530 | 0.7523 | 0.7527 | |
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| 0.1863 | 13.0 | 585 | 1.0073 | 0.7491 | 0.7468 | 0.7480 | |
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| 0.1929 | 14.0 | 630 | 1.0470 | 0.7517 | 0.7505 | 0.7511 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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