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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wnut_17 |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: modernbert-base-wnut17-english-ner |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: wnut_17 |
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type: wnut_17 |
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config: wnut_17 |
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split: test |
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args: wnut_17 |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.5518248175182482 |
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- name: Recall |
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type: recall |
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value: 0.35032437442076 |
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- name: F1 |
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type: f1 |
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value: 0.4285714285714286 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9457125758741558 |
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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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# modernbert-base-wnut17-english-ner |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the wnut_17 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5510 |
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- Precision: 0.5518 |
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- Recall: 0.3503 |
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- F1: 0.4286 |
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- Accuracy: 0.9457 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use 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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 107 | 0.3280 | 0.2601 | 0.0778 | 0.1198 | 0.9292 | |
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| No log | 2.0 | 214 | 0.2790 | 0.5609 | 0.2048 | 0.3001 | 0.9377 | |
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| No log | 3.0 | 321 | 0.2860 | 0.4403 | 0.2595 | 0.3265 | 0.9394 | |
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| No log | 4.0 | 428 | 0.3018 | 0.4534 | 0.3698 | 0.4074 | 0.9442 | |
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| 0.1707 | 5.0 | 535 | 0.3328 | 0.4742 | 0.3661 | 0.4132 | 0.9445 | |
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| 0.1707 | 6.0 | 642 | 0.4206 | 0.5119 | 0.3401 | 0.4087 | 0.9445 | |
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| 0.1707 | 7.0 | 749 | 0.4242 | 0.5238 | 0.3364 | 0.4097 | 0.9449 | |
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| 0.1707 | 8.0 | 856 | 0.4635 | 0.5624 | 0.3133 | 0.4024 | 0.9447 | |
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| 0.1707 | 9.0 | 963 | 0.4705 | 0.5432 | 0.3494 | 0.4253 | 0.9461 | |
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| 0.0052 | 10.0 | 1070 | 0.4557 | 0.4962 | 0.3652 | 0.4207 | 0.9456 | |
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| 0.0052 | 11.0 | 1177 | 0.5900 | 0.5956 | 0.3234 | 0.4192 | 0.9448 | |
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| 0.0052 | 12.0 | 1284 | 0.5206 | 0.5701 | 0.3429 | 0.4282 | 0.9456 | |
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| 0.0052 | 13.0 | 1391 | 0.5535 | 0.5805 | 0.3309 | 0.4215 | 0.9455 | |
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| 0.0052 | 14.0 | 1498 | 0.5098 | 0.5297 | 0.3559 | 0.4257 | 0.9457 | |
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| 0.0011 | 15.0 | 1605 | 0.5543 | 0.5681 | 0.3401 | 0.4255 | 0.9457 | |
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| 0.0011 | 16.0 | 1712 | 0.5394 | 0.5512 | 0.3494 | 0.4277 | 0.9456 | |
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| 0.0011 | 17.0 | 1819 | 0.5492 | 0.5577 | 0.3448 | 0.4261 | 0.9457 | |
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| 0.0011 | 18.0 | 1926 | 0.5412 | 0.5489 | 0.3540 | 0.4304 | 0.9458 | |
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| 0.0008 | 19.0 | 2033 | 0.5472 | 0.5485 | 0.3513 | 0.4282 | 0.9456 | |
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| 0.0008 | 20.0 | 2140 | 0.5510 | 0.5518 | 0.3503 | 0.4286 | 0.9457 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.1.0 |
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- Tokenizers 0.21.0 |
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