---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: bert-base-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. -->

# bert-base-cased-textCLS-RHEOLOGY

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7978
- F1: 0.6692
- Precision: 0.6343
- Recall: 0.7099
- Accuracy: 0.7099

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
| 1.365         | 1.0   | 46   | 1.1002          | 0.6205 | 0.5925    | 0.6543 | 0.6543   |
| 0.9613        | 2.0   | 92   | 0.8974          | 0.6263 | 0.6046    | 0.6605 | 0.6605   |
| 0.7465        | 3.0   | 138  | 0.7978          | 0.6692 | 0.6343    | 0.7099 | 0.7099   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3