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multibert_seed35_1311
Tommert25/multibert_seed35_1311
multibert_seed35_1311 is a token classification model from Tommert25. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023
- SHA
- 987b8c10
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
multibert_seed35_1311
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4565
- Precisions: 0.8851
- Recall: 0.8156
- F-measure: 0.8447
- Accuracy: 0.9385
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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 35
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 14
Training results
| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4595 | 1.0 | 236 | 0.2631 | 0.8847 | 0.7209 | 0.7552 | 0.9209 |
| 0.2301 | 2.0 | 472 | 0.2468 | 0.8447 | 0.7729 | 0.7954 | 0.9224 |
| 0.1332 | 3.0 | 708 | 0.2457 | 0.8468 | 0.7925 | 0.8086 | 0.9301 |
| 0.082 | 4.0 | 944 | 0.3261 | 0.8749 | 0.7855 | 0.8184 | 0.9303 |
| 0.0511 | 5.0 | 1180 | 0.3209 | 0.8952 | 0.8048 | 0.8379 | 0.9405 |
| 0.0363 | 6.0 | 1416 | 0.3568 | 0.8594 | 0.8056 | 0.8290 | 0.9337 |
| 0.0214 | 7.0 | 1652 | 0.3562 | 0.8851 | 0.8068 | 0.8350 | 0.9395 |
| 0.0152 | 8.0 | 1888 | 0.4160 | 0.8679 | 0.8065 | 0.8309 | 0.9371 |
| 0.0136 | 9.0 | 2124 | 0.4247 | 0.8732 | 0.8103 | 0.8375 | 0.9342 |
| 0.0096 | 10.0 | 2360 | 0.4242 | 0.8864 | 0.8041 | 0.8381 | 0.9378 |
| 0.0036 | 11.0 | 2596 | 0.4306 | 0.8746 | 0.8122 | 0.8365 | 0.9373 |
| 0.0029 | 12.0 | 2832 | 0.4420 | 0.8744 | 0.8220 | 0.8446 | 0.9385 |
| 0.0014 | 13.0 | 3068 | 0.4526 | 0.8850 | 0.8090 | 0.8395 | 0.9376 |
| 0.002 | 14.0 | 3304 | 0.4565 | 0.8851 | 0.8156 | 0.8447 | 0.9385 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 13, 2023
- Updated
- Nov 13, 2023