---
library_name: transformers
license: apache-2.0
base_model: cis-lmu/glot500-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: glot500_en_ewt
  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. -->

# glot500_en_ewt

This model is a fine-tuned version of [cis-lmu/glot500-base](https://huggingface.co/cis-lmu/glot500-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2637
- Precision: 0.9298
- Recall: 0.9221
- F1: 0.9259
- Accuracy: 0.9368

## 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: 16
- eval_batch_size: 16
- 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
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.399         | 1.0   | 784  | 0.3564          | 0.9169    | 0.9053 | 0.9111 | 0.9260   |
| 0.3849        | 2.0   | 1568 | 0.2637          | 0.9298    | 0.9221 | 0.9259 | 0.9368   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0