---
library_name: transformers
license: mit
base_model: deepset/gbert-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results_flausch_classification_gbert-large_span_classifier
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# results_flausch_classification_gbert-large_span_classifier

This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3241
- Accuracy: 0.9305
- F1: 0.9287

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 0.5824        | 0.6588 | 500  | 0.3772          | 0.8941   | 0.8920 |
| 0.3311        | 1.3175 | 1000 | 0.3267          | 0.9137   | 0.9124 |
| 0.2542        | 1.9763 | 1500 | 0.2943          | 0.9249   | 0.9231 |
| 0.1611        | 2.6350 | 2000 | 0.3241          | 0.9305   | 0.9287 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1