---
library_name: transformers
license: mit
base_model: deepset/gbert-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: flausch_span_gbert-large_all
  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. -->

# flausch_span_gbert-large_all

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: 0.2622
- Model Preparation Time: 0.0328
- Precision: 0.4348
- Recall: 0.5821
- F1: 0.4978

## 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 | Model Preparation Time | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|:---------:|:------:|:------:|
| 0.9007        | 0.2822 | 500  | 0.7977          | 0.0328                 | 0.0       | 0.0    | 0.0    |
| 0.7223        | 0.5643 | 1000 | 0.6214          | 0.0328                 | 0.2047    | 0.1514 | 0.1741 |
| 0.5327        | 0.8465 | 1500 | 0.4041          | 0.0328                 | 0.2262    | 0.3583 | 0.2773 |
| 0.3691        | 1.1287 | 2000 | 0.3349          | 0.0328                 | 0.2819    | 0.4330 | 0.3415 |
| 0.3021        | 1.4108 | 2500 | 0.3013          | 0.0328                 | 0.3222    | 0.4524 | 0.3764 |
| 0.2548        | 1.6930 | 3000 | 0.2655          | 0.0328                 | 0.3821    | 0.5263 | 0.4428 |
| 0.2744        | 1.9752 | 3500 | 0.2666          | 0.0328                 | 0.3072    | 0.4037 | 0.3489 |
| 0.1874        | 2.2573 | 4000 | 0.2803          | 0.0328                 | 0.4124    | 0.5461 | 0.4700 |
| 0.1767        | 2.5395 | 4500 | 0.2625          | 0.0328                 | 0.4421    | 0.5802 | 0.5018 |
| 0.1708        | 2.8217 | 5000 | 0.2622          | 0.0328                 | 0.4348    | 0.5821 | 0.4978 |


### Framework versions

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