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my_awesome_wnut_model
Tonigard/my_awesome_wnut_model
my_awesome_wnut_model is a token classification model from Tonigard. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Dec 4, 2024
- Updated
- Dec 7, 2024
- SHA
- 3ee613f6
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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. -->
my_awesome_wnut_model
This model is a fine-tuned version of cointegrated/rubert-tiny on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0046
- eval_model_preparation_time: 0.0019
- eval_precision: 0.9269
- eval_recall: 0.9588
- eval_f1: 0.9426
- eval_accuracy: 0.9987
- eval_runtime: 34.5206
- eval_samples_per_second: 1417.937
- eval_steps_per_second: 88.643
- step: 0
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
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Dec 4, 2024
- Updated
- Dec 7, 2024