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library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: slac-single-head
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. -->
# slac-single-head
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5482
- F1 Macro: 0.8380
- Precision Macro: 0.8096
- Recall Macro: 0.8688
- F1 Micro: 0.8552
- Precision Micro: 0.8252
- Recall Micro: 0.8874
## 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: 64
- eval_batch_size: 64
- seed: 42
- 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
- lr_scheduler_warmup_steps: 212
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | Precision Macro | Recall Macro | F1 Micro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|
| 0.6444 | 1.0 | 213 | 0.5045 | 0.6683 | 0.5514 | 0.9416 | 0.6611 | 0.5087 | 0.9437 |
| 0.3875 | 2.0 | 426 | 0.3121 | 0.8016 | 0.7045 | 0.9342 | 0.8214 | 0.7272 | 0.9437 |
| 0.292 | 3.0 | 639 | 0.3003 | 0.8095 | 0.7256 | 0.9294 | 0.8265 | 0.7398 | 0.9361 |
| 0.2172 | 4.0 | 852 | 0.3231 | 0.8340 | 0.7807 | 0.8982 | 0.8509 | 0.7973 | 0.9122 |
| 0.1935 | 5.0 | 1065 | 0.3262 | 0.8262 | 0.7628 | 0.9073 | 0.8445 | 0.7826 | 0.9170 |
| 0.154 | 6.0 | 1278 | 0.3807 | 0.8351 | 0.7975 | 0.8794 | 0.8506 | 0.8183 | 0.8855 |
| 0.1007 | 7.0 | 1491 | 0.4045 | 0.8297 | 0.7774 | 0.8922 | 0.8456 | 0.7902 | 0.9094 |
| 0.0866 | 8.0 | 1704 | 0.4100 | 0.8289 | 0.7706 | 0.9010 | 0.8434 | 0.7863 | 0.9094 |
| 0.0671 | 9.0 | 1917 | 0.4667 | 0.8335 | 0.7981 | 0.8726 | 0.8497 | 0.8127 | 0.8903 |
| 0.0544 | 10.0 | 2130 | 0.5062 | 0.8412 | 0.8139 | 0.8707 | 0.8557 | 0.8254 | 0.8884 |
| 0.0482 | 11.0 | 2343 | 0.5141 | 0.8335 | 0.8076 | 0.8616 | 0.8521 | 0.8287 | 0.8769 |
| 0.0377 | 12.0 | 2556 | 0.5217 | 0.8346 | 0.8022 | 0.8699 | 0.8520 | 0.8194 | 0.8874 |
| 0.0304 | 13.0 | 2769 | 0.5419 | 0.8370 | 0.8104 | 0.8658 | 0.8537 | 0.8266 | 0.8826 |
| 0.0307 | 14.0 | 2982 | 0.5397 | 0.8367 | 0.8043 | 0.8721 | 0.8533 | 0.8210 | 0.8884 |
| 0.0238 | 15.0 | 3195 | 0.5482 | 0.8380 | 0.8096 | 0.8688 | 0.8552 | 0.8252 | 0.8874 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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