---
base_model: Tommert25/robbert2909_lrate7.5
tags:
- generated_from_trainer
metrics:
- recall
- accuracy
model-index:
- name: robbert0210_lrate2.5
  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. -->

# robbert0210_lrate2.5

This model is a fine-tuned version of [Tommert25/robbert2909_lrate7.5](https://huggingface.co/Tommert25/robbert2909_lrate7.5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6768
- Precisions: 0.8111
- Recall: 0.7885
- F-measure: 0.7986
- Accuracy: 0.9113

## 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: 2.5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
| 0.054         | 1.0   | 942  | 0.6914          | 0.8256     | 0.7674 | 0.7846    | 0.9065   |
| 0.0568        | 2.0   | 1884 | 0.7397          | 0.8402     | 0.7902 | 0.8075    | 0.9099   |
| 0.0423        | 3.0   | 2826 | 0.6768          | 0.8111     | 0.7885 | 0.7986    | 0.9113   |
| 0.0293        | 4.0   | 3768 | 0.7276          | 0.8138     | 0.7879 | 0.7997    | 0.9142   |
| 0.0195        | 5.0   | 4710 | 0.7553          | 0.8036     | 0.7902 | 0.7951    | 0.9109   |
| 0.0129        | 6.0   | 5652 | 0.7606          | 0.8061     | 0.7962 | 0.7999    | 0.9100   |
| 0.0051        | 7.0   | 6594 | 0.7815          | 0.8039     | 0.7993 | 0.7996    | 0.9109   |
| 0.0104        | 8.0   | 7536 | 0.7743          | 0.8077     | 0.7986 | 0.8016    | 0.9121   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3