Downloads · 30 days
8
2% of all-time downloads
LILT-finetuned-cord_100
Saed2023/LILT-finetuned-cord_100
LILT-finetuned-cord_100 is a token classification model from Saed2023. 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. --
All-time downloads
345
Public
Repo size
2.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin521 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- lilt
- Access
- Public
- Created
- Jun 3, 2023
- Updated
- Jun 3, 2023
- SHA
- 75b65b30
Try a prompt
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. -->
LILT-finetuned-cord_100
This model is a fine-tuned version of SCUT-DLVCLab/lilt-roberta-en-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4893
- Precision: 0.9070
- Recall: 0.8864
- F1: 0.8966
- Accuracy: 0.9365
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 3.33 | 50 | 0.7078 | 0.8372 | 0.8182 | 0.8276 | 0.8889 |
| No log | 6.67 | 100 | 0.4893 | 0.9070 | 0.8864 | 0.8966 | 0.9365 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- lilt
- License
- mit
- Created
- Jun 3, 2023
- Updated
- Jun 3, 2023