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---
license: apache-2.0
base_model: jonas-luehrs/bert-base-cased-MLM-chemistry
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased-MLM-chemistry-tokenCLS-CATALYST
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# bert-base-cased-MLM-chemistry-tokenCLS-CATALYST
This model is a fine-tuned version of [jonas-luehrs/bert-base-cased-MLM-chemistry](https://huggingface.co/jonas-luehrs/bert-base-cased-MLM-chemistry) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0705
- Precision: 0.6134
- Recall: 0.8232
- F1: 0.7030
- Accuracy: 0.9775
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0945 | 1.0 | 1114 | 0.0880 | 0.5498 | 0.6406 | 0.5917 | 0.9700 |
| 0.0622 | 2.0 | 2228 | 0.0816 | 0.6515 | 0.8725 | 0.7460 | 0.9773 |
| 0.0459 | 3.0 | 3342 | 0.0705 | 0.6134 | 0.8232 | 0.7030 | 0.9775 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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