Downloads · 30 days
4
15% of all-time downloads
test_trainer
xshubhamx/test_trainer
test_trainer is a text classification model from xshubhamx. Use it when you need a label for a piece of text. 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
27
Public
Parameters
108M
433 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors433 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Apr 6, 2024
- Updated
- Apr 6, 2024
- SHA
- 85d35b66
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. -->
test_trainer
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7608
- Accuracy: 0.8172
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2825 | 1.0 | 643 | 0.8366 | 0.7359 |
| 0.7153 | 2.0 | 1286 | 0.6792 | 0.8002 |
| 0.4921 | 3.0 | 1929 | 0.7608 | 0.8172 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Apr 6, 2024
- Updated
- Apr 6, 2024