---
library_name: transformers
base_model: microsoft/mpnet-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: g-patentsberta-e2e
  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. -->

# g-patentsberta-e2e

This model is a fine-tuned version of [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4002
- Accuracy: 0.8255
- Precision: 0.2789
- Recall: 0.8247
- F1: 0.4168

## 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: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.06
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4534        | 0.1866 | 2000  | 0.4317          | 0.7988   | 0.7985    | 0.7899 | 0.7942 |
| 0.4212        | 0.3731 | 4000  | 0.4359          | 0.8043   | 0.8573    | 0.7218 | 0.7837 |
| 0.4095        | 0.5597 | 6000  | 0.4160          | 0.8157   | 0.8004    | 0.8325 | 0.8161 |
| 0.3992        | 0.7463 | 8000  | 0.4039          | 0.8210   | 0.8255    | 0.8061 | 0.8157 |
| 0.3828        | 0.9328 | 10000 | 0.3913          | 0.8241   | 0.8179    | 0.8260 | 0.8219 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2