Downloads · 30 days
11
12% of all-time downloads
xlm-roberta-base-sst2-10
tmnam20/xlm-roberta-base-sst2-10
xlm-roberta-base-sst2-10 is a text classification model from tmnam20. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
93
Public
Parameters
278M
1.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.1 GB · 98%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jan 16, 2024
- Updated
- Jan 16, 2024
- SHA
- 14860890
Try a prompt
Base models
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. -->
xlm-roberta-base-sst2-10
This model is a fine-tuned version of xlm-roberta-base on the tmnam20/VieGLUE/SST2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3909
- Accuracy: 0.8830
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: 32
- eval_batch_size: 16
- seed: 10
- 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 |
|---|---|---|---|---|
| 0.3971 | 0.24 | 500 | 0.3420 | 0.8544 |
| 0.3266 | 0.48 | 1000 | 0.3271 | 0.8555 |
| 0.2831 | 0.71 | 1500 | 0.3069 | 0.8761 |
| 0.2752 | 0.95 | 2000 | 0.3220 | 0.8807 |
| 0.2286 | 1.19 | 2500 | 0.3367 | 0.8911 |
| 0.2294 | 1.43 | 3000 | 0.3194 | 0.8761 |
| 0.2055 | 1.66 | 3500 | 0.3312 | 0.8853 |
| 0.1902 | 1.9 | 4000 | 0.3307 | 0.8842 |
| 0.1645 | 2.14 | 4500 | 0.3608 | 0.8956 |
| 0.153 | 2.38 | 5000 | 0.3796 | 0.8888 |
| 0.1868 | 2.61 | 5500 | 0.3763 | 0.8842 |
| 0.1477 | 2.85 | 6000 | 0.3959 | 0.8830 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.2.0.dev20231203+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Languages
- en
- Created
- Jan 16, 2024
- Updated
- Jan 16, 2024