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base_model: jiangg/chembert_cased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: chembert_cased-textCLS-RHEOLOGY
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. -->
# chembert_cased-textCLS-RHEOLOGY
This model is a fine-tuned version of [jiangg/chembert_cased](https://huggingface.co/jiangg/chembert_cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6766
- F1: 0.7253
- Precision: 0.7446
- Recall: 0.7407
- Accuracy: 0.7407
## 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: 32
- eval_batch_size: 32
- 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 | F1 | Precision | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
| 1.2479 | 1.0 | 46 | 0.9758 | 0.6185 | 0.5919 | 0.6605 | 0.6605 |
| 0.8039 | 2.0 | 92 | 0.7210 | 0.7277 | 0.7472 | 0.7407 | 0.7407 |
| 0.5982 | 3.0 | 138 | 0.6766 | 0.7253 | 0.7446 | 0.7407 | 0.7407 |
### Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|