---
library_name: transformers
license: mit
base_model: emanjavacas/GysBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ArjanvD95/animals_manually_curated
  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. -->

# ArjanvD95/animals_manually_curated

This model is a fine-tuned version of [emanjavacas/GysBERT](https://huggingface.co/emanjavacas/GysBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0337
- Precision: 0.7869
- Recall: 0.7912
- F1: 0.7890
- Accuracy: 0.9921

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0162        | 1.0   | 152  | 0.0321          | 0.7031    | 0.7418 | 0.7219 | 0.9886   |
| 0.0132        | 2.0   | 304  | 0.0275          | 0.7278    | 0.7198 | 0.7238 | 0.9900   |
| 0.001         | 3.0   | 456  | 0.0478          | 0.7985    | 0.5879 | 0.6772 | 0.9870   |
| 0.0015        | 4.0   | 608  | 0.0325          | 0.8095    | 0.7473 | 0.7771 | 0.9906   |
| 0.0077        | 5.0   | 760  | 0.0337          | 0.7869    | 0.7912 | 0.7890 | 0.9921   |
| 0.0003        | 6.0   | 912  | 0.0510          | 0.8621    | 0.6868 | 0.7645 | 0.9900   |
| 0.0001        | 7.0   | 1064 | 0.0517          | 0.8435    | 0.6813 | 0.7538 | 0.9899   |
| 0.0001        | 8.0   | 1216 | 0.0553          | 0.8690    | 0.6923 | 0.7706 | 0.9900   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Tokenizers 0.21.1