Downloads · 30 days
6
1% of all-time downloads
my_awesome_seq_clf_model
tristayqc/my_awesome_seq_clf_model
my_awesome_seq_clf_model is a text classification model from tristayqc. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
405
Public
Parameters
249M
2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors995 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- ibert
- Access
- Public
- Created
- Apr 25, 2024
- Updated
- Apr 25, 2024
- SHA
- a54cb6fc
Try a prompt
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_seq_clf_model
This model is a fine-tuned version of kssteven/ibert-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1998
- Accuracy: 0.9526
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1969 | 1.0 | 1563 | 0.1395 | 0.9493 |
| 0.1245 | 2.0 | 3126 | 0.1998 | 0.9526 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- ibert
- Created
- Apr 25, 2024
- Updated
- Apr 25, 2024