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distilbert-base-gest-pred-seqeval-partialmatch
Jsevisal/distilbert-base-gest-pred-seqeval-partialmatch
distilbert-base-gest-pred-seqeval-partialmatch is a token classification model from Jsevisal. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- other
- Model type
- distilbert
- Access
- Public
- Created
- Mar 27, 2023
- Updated
- Jan 21, 2025
- SHA
- fd49a79f
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Datasets
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. -->
distilbert-base-gest-pred-seqeval-partialmatch
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7454
- Precision: 0.8160
- Recall: 0.7114
- F1: 0.7404
- Accuracy: 0.8264
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.5808 | 1.0 | 147 | 1.0620 | 0.3787 | 0.3887 | 0.3730 | 0.7308 |
| 0.9003 | 2.0 | 294 | 0.8608 | 0.6557 | 0.5776 | 0.5752 | 0.7802 |
| 0.6645 | 3.0 | 441 | 0.7206 | 0.6279 | 0.5758 | 0.5768 | 0.7945 |
| 0.5084 | 4.0 | 588 | 0.6758 | 0.7613 | 0.6761 | 0.7005 | 0.8114 |
| 0.3961 | 5.0 | 735 | 0.6692 | 0.8146 | 0.7148 | 0.7431 | 0.8270 |
| 0.2992 | 6.0 | 882 | 0.7142 | 0.8092 | 0.6857 | 0.7128 | 0.8192 |
| 0.248 | 7.0 | 1029 | 0.6920 | 0.8167 | 0.7075 | 0.7395 | 0.8218 |
| 0.1984 | 8.0 | 1176 | 0.7146 | 0.8149 | 0.7297 | 0.7522 | 0.8205 |
| 0.1639 | 9.0 | 1323 | 0.7357 | 0.8175 | 0.7079 | 0.7401 | 0.8270 |
| 0.1499 | 10.0 | 1470 | 0.7454 | 0.8160 | 0.7114 | 0.7404 | 0.8264 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
LICENSE
Copyright (c) 2014, Universidad Carlos III de Madrid. Todos los derechos reservados. Este software es propiedad de la Universidad Carlos III de Madrid, grupo de investigación Robots Sociales. La Universidad Carlos III de Madrid es titular en exclusiva de los derechos de propiedad intelectual de este software. Queda prohibido cualquier uso indebido o no autorizado, entre estos, a título enunciativo pero no limitativo, la reproducción, fijación, distribución, comunicación pública, ingeniería inversa y/o transformación sobre dicho software, ya sea total o parcialmente, siendo el responsable del uso indebido o no autorizado también responsable de las consecuencias legales que pudieran derivarse de sus actos.
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- other
- Created
- Mar 27, 2023
- Updated
- Jan 21, 2025