Downloads · 30 days
10
23% of all-time downloads
distilbert-multilingual-uncased-sep-27
SmilestheSad/distilbert-multilingual-uncased-sep-27
distilbert-multilingual-uncased-sep-27 is a text classification model from SmilestheSad. 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
43
Public
Repo size
1.6 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin541 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Sep 27, 2022
- Updated
- Sep 27, 2022
- SHA
- 1e56a6fd
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. -->
distilbert-multilingual-uncased-sep-27
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0530
- F1: 0.9056
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: 4e-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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.1247 | 1.0 | 565 | 0.0661 | 0.8495 |
| 0.0533 | 2.0 | 1130 | 0.0543 | 0.8890 |
| 0.0331 | 3.0 | 1695 | 0.0530 | 0.9056 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 27, 2022
- Updated
- Sep 27, 2022