Downloads · 30 days
1
2% of all-time downloads
20230928-6-xlm-roberta-base-new
soBeauty/20230928-6-xlm-roberta-base-new
20230928-6-xlm-roberta-base-new is a fill-mask model from soBeauty. Use it when you need the model to fill a missing word. 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
42
Public
Repo size
12.2 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.1 GB · 100%
At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Sep 28, 2023
- Updated
- Sep 30, 2023
- SHA
- c542b73a
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. -->
20230928-6-xlm-roberta-base-new
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.4316
- Loss: nan
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: 8
- eval_batch_size: 8
- 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 | Accuracy | Validation Loss |
|---|---|---|---|---|
| 4.4819 | 0.46 | 200 | 0.2833 | nan |
| 4.1944 | 0.91 | 400 | 0.3591 | nan |
| 3.9494 | 1.37 | 600 | 0.3672 | nan |
| 3.6661 | 1.82 | 800 | 0.3664 | nan |
| 3.5002 | 2.28 | 1000 | 0.4206 | nan |
| 3.4947 | 2.73 | 1200 | 0.4039 | 3.3402 |
| 3.3877 | 3.19 | 1400 | 0.4462 | 2.4673 |
| 3.4862 | 3.64 | 1600 | 0.3954 | 3.2247 |
| 3.2374 | 4.1 | 1800 | 0.4565 | 2.6799 |
| 3.1623 | 4.56 | 2000 | 0.4618 | nan |
| 3.2013 | 5.01 | 2200 | 0.4556 | 2.6895 |
| 2.9187 | 5.47 | 2400 | 0.4640 | 2.7996 |
| 2.8511 | 5.92 | 2600 | 0.4878 | nan |
| 2.9993 | 6.38 | 2800 | 0.4494 | nan |
| 2.9954 | 6.83 | 3000 | 0.4606 | 2.5372 |
| 2.8736 | 7.29 | 3200 | 0.45 | 2.5804 |
| 2.7759 | 7.74 | 3400 | 0.4580 | 3.0063 |
| 2.8025 | 8.2 | 3600 | 0.4645 | 2.3861 |
| 2.9357 | 8.66 | 3800 | 0.5027 | nan |
| 2.681 | 9.11 | 4000 | 0.5 | 2.3928 |
| 2.7348 | 9.57 | 4200 | 0.4316 | nan |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Fill-Mask
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Sep 28, 2023
- Updated
- Sep 30, 2023