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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__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: 0.08916919703003628 |
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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__stsb |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init) on the GLUE STSB dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2584 |
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- Pearson: 0.0949 |
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- Spearmanr: 0.0892 |
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- Combined Score: 0.0920 |
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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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| 2.5056 | 1.0 | 45 | 2.2584 | 0.0949 | 0.0892 | 0.0920 | |
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| 2.1254 | 2.0 | 90 | 2.6871 | 0.1250 | 0.1231 | 0.1241 | |
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| 1.9839 | 3.0 | 135 | 2.2709 | 0.1790 | 0.1840 | 0.1815 | |
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| 1.6299 | 4.0 | 180 | 2.5115 | 0.2691 | 0.2797 | 0.2744 | |
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| 1.3155 | 5.0 | 225 | 2.4555 | 0.3453 | 0.3437 | 0.3445 | |
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| 0.9686 | 6.0 | 270 | 2.8004 | 0.4571 | 0.4406 | 0.4489 | |
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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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