Downloads · 30 days
7
13% of all-time downloads
unfortified_mbert
Anwaarma/unfortified_mbert
unfortified_mbert is a text classification model from Anwaarma. 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
55
Public
Parameters
178M
1.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors711 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jul 8, 2024
- Updated
- Jul 8, 2024
- SHA
- 9b085f09
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. -->
unfortified_mbert
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4362
- Accuracy: 0.78
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.0546 | 50 | 0.5973 | 0.73 |
| No log | 0.1092 | 100 | 0.6087 | 0.7 |
| No log | 0.1638 | 150 | 0.8408 | 0.64 |
| No log | 0.2183 | 200 | 0.5876 | 0.73 |
| No log | 0.2729 | 250 | 0.5553 | 0.72 |
| No log | 0.3275 | 300 | 0.4881 | 0.75 |
| No log | 0.3821 | 350 | 0.5317 | 0.75 |
| No log | 0.4367 | 400 | 0.5277 | 0.77 |
| No log | 0.4913 | 450 | 0.5430 | 0.81 |
| 0.4295 | 0.5459 | 500 | 0.5057 | 0.8 |
| 0.4295 | 0.6004 | 550 | 0.4009 | 0.78 |
| 0.4295 | 0.6550 | 600 | 0.3944 | 0.82 |
| 0.4295 | 0.7096 | 650 | 0.4829 | 0.8 |
| 0.4295 | 0.7642 | 700 | 0.4195 | 0.77 |
| 0.4295 | 0.8188 | 750 | 0.4904 | 0.8 |
| 0.4295 | 0.8734 | 800 | 0.4418 | 0.77 |
| 0.4295 | 0.9279 | 850 | 0.4362 | 0.78 |
Framework versions
- Transformers 4.42.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jul 8, 2024
- Updated
- Jul 8, 2024