Downloads · 30 days
9
13% of all-time downloads
distilbert-base-uncased-wandb-week-3-complaints-classifier-256
Kayvane/distilbert-base-uncased-wandb-week-3-complaints-classifier-256
distilbert-base-uncased-wandb-week-3-complaints-classifier-256 is a text classification model from Kayvane. 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
69
Public
Repo size
804 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin268 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jul 19, 2022
- Updated
- Jul 19, 2022
- SHA
- 88ba91c7
Try a prompt
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. -->
distilbert-base-uncased-wandb-week-3-complaints-classifier-256
This model is a fine-tuned version of distilbert-base-uncased on the consumer-finance-complaints dataset. It achieves the following results on the evaluation set:
- Loss: 0.5453
- Accuracy: 0.8235
- F1: 0.8176
- Recall: 0.8235
- Precision: 0.8171
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: 4.097565552226687e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 256
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.6691 | 0.61 | 1500 | 0.6475 | 0.7962 | 0.7818 | 0.7962 | 0.7875 |
| 0.5361 | 1.22 | 3000 | 0.5794 | 0.8161 | 0.8080 | 0.8161 | 0.8112 |
| 0.4659 | 1.83 | 4500 | 0.5453 | 0.8235 | 0.8176 | 0.8235 | 0.8171 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jul 19, 2022
- Updated
- Jul 19, 2022