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--- |
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license: apache-2.0 |
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base_model: jonas-luehrs/bert-base-uncased-MLP-scirepeval-chemistry-LARGE |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: bert-base-uncased-MLP-scirepeval-chemistry-LARGE-textCLS-RHEOLOGY-20230913-3 |
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results: [] |
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datasets: |
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- bluesky333/chemical_language_understanding_benchmark |
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language: |
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- en |
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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-uncased-MLP-scirepeval-chemistry-LARGE-textCLS-RHEOLOGY-20230913-3 |
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This model is a fine-tuned version of [jonas-luehrs/bert-base-uncased-MLP-scirepeval-chemistry-LARGE](https://huggingface.co/jonas-luehrs/bert-base-uncased-MLP-scirepeval-chemistry-LARGE) on the RHEOLOGY dataset of the [blue333/chemical_language_understanding_benchmark](https://huggingface.co/datasets/bluesky333/chemical_language_understanding_benchmark). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6836 |
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- F1: 0.7805 |
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- Precision: 0.7860 |
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- Recall: 0.7840 |
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- Accuracy: 0.7840 |
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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: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:| |
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| 1.1777 | 1.0 | 46 | 0.8465 | 0.6593 | 0.6346 | 0.7037 | 0.7037 | |
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| 0.6923 | 2.0 | 92 | 0.7123 | 0.7491 | 0.7654 | 0.7593 | 0.7593 | |
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| 0.4974 | 3.0 | 138 | 0.6906 | 0.7563 | 0.7667 | 0.7593 | 0.7593 | |
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| 0.3789 | 4.0 | 184 | 0.6754 | 0.7645 | 0.7712 | 0.7716 | 0.7716 | |
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| 0.3053 | 5.0 | 230 | 0.6836 | 0.7805 | 0.7860 | 0.7840 | 0.7840 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
