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thermo-predictor-thermo-evotuning-prot_bert

Text Classification
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PyTorch
bert
Generated from Trainer
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - spearmanr
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+ model-index:
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+ - name: thermo-predictor-thermo-evotuning-prot_bert
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+ results: []
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+ ---
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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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+
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+ # thermo-predictor-thermo-evotuning-prot_bert
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+
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+ This model is a fine-tuned version of [thundaa/thermo-evotuning-prot_bert](https://huggingface.co/thundaa/thermo-evotuning-prot_bert) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1617
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+ - Spearmanr: 0.6914
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 256
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+ - eval_batch_size: 256
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+ - seed: 42
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+ - gradient_accumulation_steps: 64
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+ - total_train_batch_size: 16384
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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: 1
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Spearmanr |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|
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+ | 0.4734 | 0.68 | 2 | 0.3146 | 0.3359 |
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+ | 0.4392 | 1.68 | 4 | 0.2936 | 0.3407 |
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+ | 0.4034 | 2.68 | 6 | 0.2633 | 0.3696 |
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+ | 0.3669 | 3.68 | 8 | 0.2437 | 0.3903 |
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+ | 0.3496 | 4.68 | 10 | 0.2377 | 0.4102 |
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+ | 0.3351 | 5.68 | 12 | 0.2285 | 0.4204 |
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+ | 0.3289 | 6.68 | 14 | 0.2267 | 0.4180 |
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+ | 0.3267 | 7.68 | 16 | 0.2258 | 0.4242 |
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+ | 0.3177 | 8.68 | 18 | 0.2206 | 0.4295 |
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+ | 0.3116 | 9.68 | 20 | 0.2150 | 0.4365 |
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+ | 0.3039 | 10.68 | 22 | 0.2115 | 0.4365 |
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+ | 0.2985 | 11.68 | 24 | 0.2062 | 0.4469 |
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+ | 0.2927 | 12.68 | 26 | 0.2045 | 0.4531 |
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+ | 0.2885 | 13.68 | 28 | 0.2005 | 0.4603 |
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+ | 0.2838 | 14.68 | 30 | 0.1987 | 0.4690 |
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+ | 0.2806 | 15.68 | 32 | 0.1975 | 0.4744 |
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+ | 0.2772 | 16.68 | 34 | 0.1970 | 0.4765 |
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+ | 0.2728 | 17.68 | 36 | 0.1939 | 0.4845 |
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+ | 0.2684 | 18.68 | 38 | 0.1931 | 0.4858 |
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+ | 0.2641 | 19.68 | 40 | 0.1925 | 0.4936 |
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+ | 0.2608 | 20.68 | 42 | 0.1905 | 0.4929 |
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+ | 0.2566 | 21.68 | 44 | 0.1886 | 0.5049 |
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+ | 0.2518 | 22.68 | 46 | 0.1875 | 0.5095 |
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+ | 0.2467 | 23.68 | 48 | 0.1869 | 0.5141 |
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+ | 0.2424 | 24.68 | 50 | 0.1859 | 0.5161 |
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+ | 0.2375 | 25.68 | 52 | 0.1850 | 0.5223 |
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+ | 0.2329 | 26.68 | 54 | 0.1851 | 0.5210 |
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+ | 0.2279 | 27.68 | 56 | 0.1850 | 0.5294 |
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+ | 0.2226 | 28.68 | 58 | 0.1837 | 0.5310 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.18.0
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+ - Pytorch 1.11.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.12.1