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README.md
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---
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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_48_emb_com_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
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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: 0.4507892146083376
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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_48_emb_com_stsb
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_emb_compress_48) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.9571
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- Pearson: 0.4588
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- Spearmanr: 0.4508
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- Combined Score: 0.4548
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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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| 2.5817 | 1.0 | 45 | 2.6028 | 0.2027 | 0.1896 | 0.1962 |
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| 2.1023 | 2.0 | 90 | 2.1596 | 0.2035 | 0.1938 | 0.1986 |
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| 1.9567 | 3.0 | 135 | 2.3409 | 0.1855 | 0.1931 | 0.1893 |
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| 1.7201 | 4.0 | 180 | 2.1790 | 0.2865 | 0.2934 | 0.2899 |
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| 1.5153 | 5.0 | 225 | 2.1208 | 0.3381 | 0.3352 | 0.3367 |
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| 1.2674 | 6.0 | 270 | 2.1224 | 0.3882 | 0.3898 | 0.3890 |
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| 1.0115 | 7.0 | 315 | 2.2253 | 0.4304 | 0.4281 | 0.4293 |
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| 0.7449 | 8.0 | 360 | 2.3235 | 0.4236 | 0.4323 | 0.4279 |
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| 0.66 | 9.0 | 405 | 2.3617 | 0.4340 | 0.4351 | 0.4346 |
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| 0.4678 | 10.0 | 450 | 2.0741 | 0.4300 | 0.4258 | 0.4279 |
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| 0.4438 | 11.0 | 495 | 2.3816 | 0.4285 | 0.4294 | 0.4289 |
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| 0.3192 | 12.0 | 540 | 2.1673 | 0.4580 | 0.4602 | 0.4591 |
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| 0.2481 | 13.0 | 585 | 2.1544 | 0.4392 | 0.4357 | 0.4374 |
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| 0.2296 | 14.0 | 630 | 2.0075 | 0.4603 | 0.4582 | 0.4593 |
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| 0.1765 | 15.0 | 675 | 2.1395 | 0.4624 | 0.4617 | 0.4621 |
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| 0.1533 | 16.0 | 720 | 2.2715 | 0.4512 | 0.4427 | 0.4469 |
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| 0.1343 | 17.0 | 765 | 2.1726 | 0.4441 | 0.4417 | 0.4429 |
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| 0.1373 | 18.0 | 810 | 2.0223 | 0.4532 | 0.4424 | 0.4478 |
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| 0.1277 | 19.0 | 855 | 1.9992 | 0.4395 | 0.4299 | 0.4347 |
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| 0.0968 | 20.0 | 900 | 2.1078 | 0.4620 | 0.4601 | 0.4610 |
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| 0.084 | 21.0 | 945 | 2.0684 | 0.4627 | 0.4577 | 0.4602 |
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| 0.0777 | 22.0 | 990 | 1.9214 | 0.4648 | 0.4600 | 0.4624 |
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| 0.0572 | 23.0 | 1035 | 2.0636 | 0.4506 | 0.4422 | 0.4464 |
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| 0.0615 | 24.0 | 1080 | 2.0404 | 0.4489 | 0.4388 | 0.4438 |
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| 0.0516 | 25.0 | 1125 | 2.0599 | 0.4516 | 0.4435 | 0.4475 |
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| 0.0501 | 26.0 | 1170 | 2.0359 | 0.4530 | 0.4489 | 0.4510 |
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| 0.0515 | 27.0 | 1215 | 1.9571 | 0.4588 | 0.4508 | 0.4548 |
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### Framework versions
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- Transformers 4.30.2
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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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