Downloads · 30 days
16
37% of all-time downloads
SiddharthaM/mbert-targin-final
mbert-targin-final is a text classification model from SiddharthaM. 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. --
Downloads · 30 days
16
37% of all-time downloads
All-time downloads
43
Public
Repo size
5 GB
Likes
0
Public
Click a slice to open those files.
.bin711 MB · 99%
From the Hugging Face model README
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 296 | 0.5774 | 0.7091 | 0.6506 | 0.6378 | 0.6426 |
| 0.5912 | 2.0 | 592 | 0.5316 | 0.7376 | 0.6880 | 0.6767 | 0.6814 |
| 0.5912 | 3.0 | 888 | 0.5511 | 0.7253 | 0.6692 | 0.6293 | 0.6378 |
| 0.4844 | 4.0 | 1184 | 0.6262 | 0.6835 | 0.6622 | 0.6884 | 0.6613 |
| 0.4844 | 5.0 | 1480 | 0.6320 | 0.7006 | 0.6574 | 0.6701 | 0.6616 |
| 0.3861 | 6.0 | 1776 | 0.6983 | 0.7148 | 0.6632 | 0.6620 | 0.6626 |
| 0.2773 | 7.0 | 2072 | 0.8109 | 0.7110 | 0.6630 | 0.6689 | 0.6655 |
| 0.2773 | 8.0 | 2368 | 0.8948 | 0.7072 | 0.6525 | 0.6487 | 0.6504 |
| 0.2068 | 9.0 | 2664 | 0.9693 | 0.7072 | 0.6519 | 0.6469 | 0.6492 |
| 0.2068 | 10.0 | 2960 | 0.9847 | 0.7025 | 0.6490 | 0.6487 | 0.6489 |