File size: 3,240 Bytes
c839b2d | 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 | ---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: fred-guard-base
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. -->
# fred-guard-base
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0508
- Accuracy: 0.9806
- Precision: 1.0
- Recall: 0.9611
- F1: 0.9802
## 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: 64
- eval_batch_size: 32
- 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
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.9662 | 0.1111 | 5 | 0.7300 | 0.5194 | 0.5099 | 1.0 | 0.6754 |
| 0.6438 | 0.2222 | 10 | 0.5574 | 0.6778 | 0.6553 | 0.75 | 0.6995 |
| 0.6016 | 0.3333 | 15 | 0.4892 | 0.7667 | 0.8038 | 0.7056 | 0.7515 |
| 0.4617 | 0.4444 | 20 | 0.4301 | 0.7972 | 0.7512 | 0.8889 | 0.8142 |
| 0.3779 | 0.5556 | 25 | 0.3152 | 0.8528 | 0.8588 | 0.8444 | 0.8515 |
| 0.3712 | 0.6667 | 30 | 0.2228 | 0.8944 | 0.9437 | 0.8389 | 0.8882 |
| 0.2169 | 0.7778 | 35 | 0.2674 | 0.8806 | 0.9928 | 0.7667 | 0.8652 |
| 0.2445 | 0.8889 | 40 | 0.1471 | 0.9306 | 0.9189 | 0.9444 | 0.9315 |
| 0.1838 | 1.0 | 45 | 0.2446 | 0.8833 | 0.9929 | 0.7722 | 0.8688 |
| 0.1249 | 1.1111 | 50 | 0.1212 | 0.9472 | 0.9215 | 0.9778 | 0.9488 |
| 0.0775 | 1.2222 | 55 | 0.1005 | 0.9556 | 0.9940 | 0.9167 | 0.9538 |
| 0.0776 | 1.3333 | 60 | 0.0783 | 0.9722 | 0.9775 | 0.9667 | 0.9721 |
| 0.0577 | 1.4444 | 65 | 0.0924 | 0.9722 | 0.9942 | 0.95 | 0.9716 |
| 0.0753 | 1.5556 | 70 | 0.0763 | 0.9722 | 0.9942 | 0.95 | 0.9716 |
| 0.0733 | 1.6667 | 75 | 0.0453 | 0.975 | 0.9831 | 0.9667 | 0.9748 |
| 0.0866 | 1.7778 | 80 | 0.0576 | 0.9778 | 1.0 | 0.9556 | 0.9773 |
| 0.041 | 1.8889 | 85 | 0.0583 | 0.9778 | 1.0 | 0.9556 | 0.9773 |
| 0.0579 | 2.0 | 90 | 0.0508 | 0.9806 | 1.0 | 0.9611 | 0.9802 |
### Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|