File size: 3,489 Bytes
cb26e00 b968895 cb26e00 b968895 cb26e00 b968895 cb26e00 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 | ---
library_name: transformers
license: apache-2.0
base_model: TomasFAV/BERTInvoiceCzechV0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERTInvoiceCzechV03
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. -->
# BERTInvoiceCzechV03
This model is a fine-tuned version of [TomasFAV/BERTInvoiceCzechV0](https://huggingface.co/TomasFAV/BERTInvoiceCzechV0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0683
- Precision: 0.8635
- Recall: 0.8866
- F1: 0.8749
- Accuracy: 0.9833
## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 2
- 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: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 20 | 0.1657 | 0.6566 | 0.7456 | 0.6983 | 0.9547 |
| No log | 2.0 | 40 | 0.1222 | 0.7308 | 0.7821 | 0.7556 | 0.9653 |
| No log | 3.0 | 60 | 0.1044 | 0.7512 | 0.8233 | 0.7856 | 0.9707 |
| No log | 4.0 | 80 | 0.0872 | 0.7799 | 0.8532 | 0.8149 | 0.9747 |
| No log | 5.0 | 100 | 0.0897 | 0.7791 | 0.8808 | 0.8268 | 0.9748 |
| No log | 6.0 | 120 | 0.0850 | 0.7725 | 0.8730 | 0.8197 | 0.9742 |
| No log | 7.0 | 140 | 0.0704 | 0.8433 | 0.88 | 0.8613 | 0.9812 |
| No log | 8.0 | 160 | 0.0749 | 0.8291 | 0.8649 | 0.8466 | 0.9799 |
| No log | 9.0 | 180 | 0.0752 | 0.8187 | 0.8753 | 0.8461 | 0.9794 |
| No log | 10.0 | 200 | 0.0687 | 0.8440 | 0.8761 | 0.8598 | 0.9815 |
| No log | 11.0 | 220 | 0.0671 | 0.8436 | 0.8816 | 0.8621 | 0.9820 |
| No log | 12.0 | 240 | 0.0711 | 0.8376 | 0.8913 | 0.8636 | 0.9809 |
| No log | 13.0 | 260 | 0.0683 | 0.8638 | 0.8870 | 0.8753 | 0.9833 |
| No log | 14.0 | 280 | 0.0686 | 0.8488 | 0.8870 | 0.8675 | 0.9818 |
| No log | 15.0 | 300 | 0.0690 | 0.8439 | 0.8816 | 0.8623 | 0.9816 |
| No log | 16.0 | 320 | 0.0669 | 0.8469 | 0.8827 | 0.8644 | 0.9819 |
| No log | 17.0 | 340 | 0.0699 | 0.8404 | 0.8897 | 0.8644 | 0.9814 |
| No log | 18.0 | 360 | 0.0684 | 0.8532 | 0.8870 | 0.8698 | 0.9825 |
| No log | 19.0 | 380 | 0.0701 | 0.8408 | 0.8920 | 0.8656 | 0.9815 |
| No log | 20.0 | 400 | 0.0685 | 0.8560 | 0.8909 | 0.8731 | 0.9827 |
### Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
|