File size: 2,188 Bytes
73985ad |
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 |
---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: eternis_router_encoder_sft_4Sep
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. -->
# eternis_router_encoder_sft_4Sep
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: 0.1710
- Mse: 0.1710
- Model Accuracy: 0.3285
## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mse | Model Accuracy |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------------:|
| 0.4021 | 0.3429 | 300 | 0.1875 | 0.1875 | 0.153 |
| 0.3702 | 0.6857 | 600 | 0.1809 | 0.1809 | 0.1757 |
| 0.36 | 1.0286 | 900 | 0.1762 | 0.1762 | 0.3068 |
| 0.3686 | 1.3714 | 1200 | 0.1788 | 0.1788 | 0.2333 |
| 0.3337 | 1.7143 | 1500 | 0.1733 | 0.1733 | 0.3192 |
| 0.3293 | 2.0571 | 1800 | 0.1709 | 0.1709 | 0.3297 |
| 0.3245 | 2.4 | 2100 | 0.1706 | 0.1706 | 0.3035 |
| 0.3158 | 2.7429 | 2400 | 0.1710 | 0.1710 | 0.3285 |
### Framework versions
- Transformers 4.56.0
- Pytorch 2.7.0
- Datasets 4.0.0
- Tokenizers 0.22.0
|