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library_name: transformers
language:
- en
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: DisambertSingleSense-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. -->
# DisambertSingleSense-base
This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the semcor dataset.
It achieves the following results on the evaluation set:
- Loss: 10.3845
- Precision: 0.9250
- Recall: 0.5786
- F1: 0.7119
- Accuracy: 0.6008
- Matthews: 0.6006
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Matthews |
|:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|:--------:|
| No log | 0 | 0 | 207.0982 | 0.0 | 0.0 | 0.0 | 0.0 | -0.0000 |
| 11.1217 | 1.0 | 14014 | 15.0481 | 0.9215 | 0.5209 | 0.6656 | 0.4562 | 0.4558 |
| 5.9994 | 2.0 | 28028 | 10.3853 | 0.7928 | 0.3539 | 0.4894 | 0.4978 | 0.4979 |
| 3.7236 | 3.0 | 42042 | 8.8450 | 0.9086 | 0.5679 | 0.6989 | 0.5570 | 0.5566 |
| 2.5493 | 4.0 | 56056 | 8.7346 | 0.9313 | 0.5675 | 0.7053 | 0.5793 | 0.5790 |
| 1.9121 | 5.0 | 70070 | 8.9990 | 0.9163 | 0.5669 | 0.7004 | 0.5701 | 0.5698 |
| 0.9166 | 6.0 | 84084 | 9.2895 | 0.9287 | 0.5799 | 0.7139 | 0.5815 | 0.5812 |
| 0.8231 | 7.0 | 98098 | 9.3043 | 0.9185 | 0.5844 | 0.7143 | 0.5907 | 0.5904 |
| 0.4919 | 8.0 | 112112 | 9.7527 | 0.9216 | 0.5668 | 0.7019 | 0.5802 | 0.5799 |
| 0.5579 | 9.0 | 126126 | 9.9372 | 0.9265 | 0.5745 | 0.7092 | 0.5929 | 0.5926 |
| 0.3221 | 10.0 | 140140 | 10.1643 | 0.9254 | 0.5726 | 0.7074 | 0.5868 | 0.5865 |
| 0.4007 | 11.0 | 154154 | 10.1666 | 0.9077 | 0.5722 | 0.7019 | 0.5885 | 0.5882 |
| 0.1726 | 12.0 | 168168 | 10.3202 | 0.9179 | 0.5691 | 0.7026 | 0.5894 | 0.5891 |
| 0.2729 | 13.0 | 182182 | 10.4281 | 0.9127 | 0.5648 | 0.6978 | 0.5916 | 0.5913 |
| 0.1867 | 14.0 | 196196 | 10.3487 | 0.9042 | 0.5731 | 0.7016 | 0.5951 | 0.5948 |
| 0.1512 | 15.0 | 210210 | 10.2347 | 0.9262 | 0.5742 | 0.7089 | 0.5968 | 0.5966 |
| 0.1377 | 16.0 | 224224 | 10.3734 | 0.9211 | 0.5772 | 0.7097 | 0.6017 | 0.6014 |
| 0.2627 | 17.0 | 238238 | 10.5554 | 0.9212 | 0.5767 | 0.7093 | 0.5990 | 0.5988 |
| 0.1610 | 18.0 | 252252 | 10.4423 | 0.9273 | 0.5748 | 0.7097 | 0.6008 | 0.6006 |
| 0.1973 | 19.0 | 266266 | 10.6396 | 0.9289 | 0.5729 | 0.7087 | 0.5947 | 0.5945 |
| 0.1504 | 20.0 | 280280 | 10.5432 | 0.9132 | 0.5740 | 0.7049 | 0.5995 | 0.5992 |
| 0.0363 | 21.0 | 294294 | 10.6388 | 0.9291 | 0.5744 | 0.7099 | 0.5986 | 0.5984 |
| 0.0384 | 22.0 | 308308 | 10.5433 | 0.9314 | 0.5750 | 0.7111 | 0.5977 | 0.5975 |
| 0.0792 | 23.0 | 322322 | 10.7152 | 0.9308 | 0.5752 | 0.7110 | 0.5995 | 0.5994 |
| 0.0165 | 24.0 | 336336 | 10.6516 | 0.9301 | 0.5690 | 0.7061 | 0.5964 | 0.5962 |
| 0.0644 | 25.0 | 350350 | 10.3666 | 0.9297 | 0.5788 | 0.7134 | 0.6012 | 0.6010 |
| 0.0246 | 26.0 | 364364 | 10.3480 | 0.9285 | 0.5700 | 0.7064 | 0.5947 | 0.5945 |
| 0.0518 | 27.0 | 378378 | 10.6784 | 0.9300 | 0.5783 | 0.7131 | 0.5977 | 0.5975 |
| 0.0267 | 28.0 | 392392 | 10.7434 | 0.9306 | 0.5742 | 0.7102 | 0.5999 | 0.5998 |
| 0.0847 | 29.0 | 406406 | 10.4787 | 0.9289 | 0.5787 | 0.7131 | 0.6017 | 0.6014 |
| 0.0923 | 30.0 | 420420 | 10.3845 | 0.9250 | 0.5786 | 0.7119 | 0.6008 | 0.6006 |
### Framework versions
- Transformers 5.1.0
- Pytorch 2.6.0+cu124
- Datasets 4.5.0
- Tokenizers 0.22.2
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