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my_awesome_wnut_all_NEG
gonzalezrostani/my_awesome_wnut_all_NEG
my_awesome_wnut_all_NEG is a token classification model from gonzalezrostani. 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
- distilbert
- Access
- Public
- Created
- Mar 24, 2024
- Updated
- Mar 24, 2024
- SHA
- 80222b80
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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_all_NEG
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0175
- Precision: 0.7955
- Recall: 0.8537
- F1: 0.8235
- Accuracy: 0.9948
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 251 | 0.0170 | 0.8056 | 0.8488 | 0.8266 | 0.9948 |
| 0.0275 | 2.0 | 502 | 0.0166 | 0.7937 | 0.8634 | 0.8271 | 0.9948 |
| 0.0275 | 3.0 | 753 | 0.0169 | 0.7982 | 0.8683 | 0.8318 | 0.9947 |
| 0.0083 | 4.0 | 1004 | 0.0175 | 0.7955 | 0.8537 | 0.8235 | 0.9948 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 24, 2024
- Updated
- Mar 24, 2024