metadata
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: []
glot500_en_ewt
This model is a fine-tuned version of 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