modernbert-match-user-52991
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6696
- Accuracy: 0.6585
- F1: 0.6472
- Precision: 0.6443
- Recall: 0.6585
- F1 Class 0: 0.4138
- F1 Class 1: 0.2667
- F1 Class 2: 0.1176
- F1 Class 3: 0.0952
- F1 Class 4: 0.8659
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: 4
- eval_batch_size: 4
- 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: cosine_with_restarts
- lr_scheduler_warmup_steps: 123
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | F1 Class 0 | F1 Class 1 | F1 Class 2 | F1 Class 3 | F1 Class 4 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1.2013 | 1.0 | 123 | 0.9732 | 0.6260 | 0.5735 | 0.5618 | 0.6260 | 0.2 | 0.0909 | 0.0 | 0.0 | 0.8409 |
1.0426 | 2.0 | 246 | 1.0982 | 0.6667 | 0.5515 | 0.5239 | 0.6667 | 0.3 | 0.0 | 0.0 | 0.0 | 0.7980 |
0.8163 | 3.0 | 369 | 1.0723 | 0.6260 | 0.5949 | 0.6142 | 0.6260 | 0.3 | 0.0 | 0.0 | 0.0 | 0.8655 |
0.6124 | 4.0 | 492 | 1.6696 | 0.6585 | 0.6472 | 0.6443 | 0.6585 | 0.4138 | 0.2667 | 0.1176 | 0.0952 | 0.8659 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0
- Datasets 2.21.0
- Tokenizers 0.21.0
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Base model
answerdotai/ModernBERT-base