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

# gbert-large-topic_classification

This model is a fine-tuned version of [deepset/gbert-large](https://huggingface.co/deepset/gbert-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5093
- Precision: 0.9100
- Recall: 0.8993
- F1: 0.9042
- Accuracy: 0.9167

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 44   | 0.6465          | 0.8897    | 0.8138 | 0.8179 | 0.8480   |
| No log        | 2.0   | 88   | 0.2949          | 0.9116    | 0.9110 | 0.9106 | 0.9118   |
| No log        | 3.0   | 132  | 0.4110          | 0.9298    | 0.8939 | 0.9020 | 0.9167   |
| No log        | 4.0   | 176  | 0.6242          | 0.9261    | 0.8756 | 0.8911 | 0.9020   |
| No log        | 5.0   | 220  | 0.5606          | 0.9208    | 0.8757 | 0.8897 | 0.9020   |
| No log        | 6.0   | 264  | 0.6164          | 0.9201    | 0.8867 | 0.9001 | 0.9069   |
| No log        | 7.0   | 308  | 0.4898          | 0.9155    | 0.9001 | 0.9071 | 0.9167   |
| No log        | 8.0   | 352  | 0.4999          | 0.9191    | 0.9029 | 0.9102 | 0.9216   |
| No log        | 9.0   | 396  | 0.5073          | 0.9100    | 0.8993 | 0.9042 | 0.9167   |
| No log        | 10.0  | 440  | 0.5093          | 0.9100    | 0.8993 | 0.9042 | 0.9167   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1