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--- |
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library_name: transformers |
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license: mit |
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base_model: chandar-lab/NeoBERT |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: NeoBERT-multiclass-classifier-ICLR |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# NeoBERT-multiclass-classifier-ICLR |
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This model is a fine-tuned version of [chandar-lab/NeoBERT](https://huggingface.co/chandar-lab/NeoBERT) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7258 |
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- F1: 0.5134 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 45 | 1.2609 | 0.4641 | |
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| No log | 2.0 | 90 | 1.3167 | 0.4641 | |
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| 1.2441 | 3.0 | 135 | 1.1799 | 0.5405 | |
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| 1.2441 | 4.0 | 180 | 1.2810 | 0.5386 | |
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| 1.0526 | 5.0 | 225 | 1.2742 | 0.5098 | |
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| 1.0526 | 6.0 | 270 | 1.4929 | 0.5030 | |
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| 0.7789 | 7.0 | 315 | 1.5076 | 0.5425 | |
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| 0.7789 | 8.0 | 360 | 1.6513 | 0.4908 | |
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| 0.5299 | 9.0 | 405 | 1.6172 | 0.5476 | |
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| 0.5299 | 10.0 | 450 | 1.7358 | 0.5389 | |
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| 0.5299 | 11.0 | 495 | 1.8935 | 0.4847 | |
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| 0.4185 | 12.0 | 540 | 1.8012 | 0.5152 | |
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| 0.4185 | 13.0 | 585 | 1.7241 | 0.5337 | |
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| 0.3614 | 14.0 | 630 | 1.7109 | 0.5257 | |
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| 0.3614 | 15.0 | 675 | 1.7233 | 0.5024 | |
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| 0.3527 | 16.0 | 720 | 1.7104 | 0.5147 | |
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| 0.3527 | 17.0 | 765 | 1.7282 | 0.5134 | |
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| 0.3513 | 18.0 | 810 | 1.7257 | 0.5134 | |
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| 0.3513 | 19.0 | 855 | 1.7263 | 0.5134 | |
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| 0.3511 | 20.0 | 900 | 1.7258 | 0.5134 | |
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### Framework versions |
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- Transformers 4.53.0 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.2 |
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