---
library_name: transformers
base_model: FPTAI/velectra-base-discriminator-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: velectra-base_v2
  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. -->

# velectra-base_v2

This model is a fine-tuned version of [FPTAI/velectra-base-discriminator-cased](https://huggingface.co/FPTAI/velectra-base-discriminator-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5503
- Accuracy: 0.9242
- Precision Macro: 0.8370
- Recall Macro: 0.7946
- F1 Macro: 0.8125
- F1 Weighted: 0.9222

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use 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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:-----------:|
| 0.5452        | 1.0   | 90   | 0.2734          | 0.9071   | 0.8647          | 0.6926       | 0.7190   | 0.8965      |
| 0.2546        | 2.0   | 180  | 0.2530          | 0.9198   | 0.8318          | 0.7882       | 0.8059   | 0.9176      |
| 0.1788        | 3.0   | 270  | 0.2528          | 0.9223   | 0.8241          | 0.7732       | 0.7929   | 0.9193      |
| 0.1323        | 4.0   | 360  | 0.2605          | 0.9261   | 0.8473          | 0.8000       | 0.8197   | 0.9241      |
| 0.0901        | 5.0   | 450  | 0.2840          | 0.9305   | 0.8839          | 0.7986       | 0.8303   | 0.9276      |
| 0.0682        | 6.0   | 540  | 0.3434          | 0.9210   | 0.8458          | 0.8007       | 0.8197   | 0.9192      |
| 0.0482        | 7.0   | 630  | 0.3689          | 0.9191   | 0.7970          | 0.8197       | 0.8073   | 0.9206      |
| 0.0443        | 8.0   | 720  | 0.3906          | 0.9223   | 0.8315          | 0.7728       | 0.7952   | 0.9191      |
| 0.0275        | 9.0   | 810  | 0.4178          | 0.9210   | 0.8717          | 0.7504       | 0.7861   | 0.9155      |
| 0.028         | 10.0  | 900  | 0.4642          | 0.9103   | 0.7837          | 0.7837       | 0.7835   | 0.9103      |
| 0.02          | 11.0  | 990  | 0.4823          | 0.9179   | 0.8459          | 0.7694       | 0.7971   | 0.9143      |
| 0.0122        | 12.0  | 1080 | 0.5070          | 0.9179   | 0.8594          | 0.7853       | 0.8136   | 0.9151      |
| 0.0098        | 13.0  | 1170 | 0.5093          | 0.9248   | 0.8387          | 0.7911       | 0.8106   | 0.9225      |
| 0.0108        | 14.0  | 1260 | 0.5309          | 0.9248   | 0.8678          | 0.7783       | 0.8098   | 0.9212      |
| 0.0101        | 15.0  | 1350 | 0.5214          | 0.9261   | 0.8623          | 0.7669       | 0.7986   | 0.9216      |
| 0.0076        | 16.0  | 1440 | 0.5352          | 0.9242   | 0.8653          | 0.7737       | 0.8054   | 0.9203      |
| 0.0042        | 17.0  | 1530 | 0.5533          | 0.9198   | 0.8163          | 0.7870       | 0.8000   | 0.9181      |
| 0.0058        | 18.0  | 1620 | 0.5503          | 0.9255   | 0.8574          | 0.7871       | 0.8138   | 0.9225      |
| 0.0034        | 19.0  | 1710 | 0.5590          | 0.9248   | 0.8349          | 0.8035       | 0.8173   | 0.9233      |
| 0.0029        | 20.0  | 1800 | 0.5503          | 0.9242   | 0.8370          | 0.7946       | 0.8125   | 0.9222      |


### Framework versions

- Transformers 4.55.0
- Pytorch 2.7.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4