Downloads · 30 days
6
12% of all-time downloads
my_awesome_wnut_model
sarahh23/my_awesome_wnut_model
my_awesome_wnut_model is a token classification model from sarahh23. 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. --
All-time downloads
49
Public
Parameters
66.4M
4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors266 MB · 100%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jul 19, 2024
- Updated
- Jul 20, 2024
- SHA
- 7a8de28c
Try a prompt
Base models
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. -->
my_awesome_wnut_model
This model is a fine-tuned version of distilbert-base-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2885
- Precision: 0.5508
- Recall: 0.3818
- F1: 0.4510
- Accuracy: 0.9464
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 213 | 0.2879 | 0.5754 | 0.2122 | 0.3101 | 0.9378 |
| No log | 2.0 | 426 | 0.2657 | 0.5796 | 0.3207 | 0.4129 | 0.9435 |
| 0.1879 | 3.0 | 639 | 0.2710 | 0.5795 | 0.3411 | 0.4294 | 0.9452 |
| 0.1879 | 4.0 | 852 | 0.2823 | 0.5811 | 0.3587 | 0.4436 | 0.9461 |
| 0.0543 | 5.0 | 1065 | 0.2885 | 0.5508 | 0.3818 | 0.4510 | 0.9464 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jul 19, 2024
- Updated
- Jul 20, 2024