Downloads · 30 days
6
11% of all-time downloads
xlm-roberta-base_hau_corr_2e-05
Shijia/xlm-roberta-base_hau_corr_2e-05
xlm-roberta-base_hau_corr_2e-05 is a text classification model from Shijia. 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
53
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
- Feb 17, 2024
- Updated
- Feb 17, 2024
- SHA
- 9b1e4325
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. -->
xlm-roberta-base_hau_corr_2e-05
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0218
- Spearman Corr: 0.7816
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: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|---|---|---|---|---|
| No log | 0.95 | 200 | 0.0215 | 0.7799 |
| No log | 1.91 | 400 | 0.0226 | 0.7758 |
| 0.0008 | 2.86 | 600 | 0.0218 | 0.7788 |
| 0.0008 | 3.82 | 800 | 0.0213 | 0.7793 |
| 0.0008 | 4.77 | 1000 | 0.0213 | 0.7786 |
| 0.0008 | 5.73 | 1200 | 0.0224 | 0.7798 |
| 0.0007 | 6.68 | 1400 | 0.0215 | 0.7808 |
| 0.0007 | 7.64 | 1600 | 0.0213 | 0.7792 |
| 0.0007 | 8.59 | 1800 | 0.0208 | 0.7802 |
| 0.0007 | 9.55 | 2000 | 0.0221 | 0.7777 |
| 0.0006 | 10.5 | 2200 | 0.0210 | 0.7797 |
| 0.0006 | 11.46 | 2400 | 0.0207 | 0.7799 |
| 0.0006 | 12.41 | 2600 | 0.0213 | 0.7805 |
| 0.0006 | 13.37 | 2800 | 0.0219 | 0.7825 |
| 0.0006 | 14.32 | 3000 | 0.0209 | 0.7799 |
| 0.0006 | 15.27 | 3200 | 0.0214 | 0.7818 |
| 0.0005 | 16.23 | 3400 | 0.0210 | 0.7811 |
| 0.0005 | 17.18 | 3600 | 0.0216 | 0.7803 |
| 0.0005 | 18.14 | 3800 | 0.0215 | 0.7807 |
| 0.0005 | 19.09 | 4000 | 0.0210 | 0.7793 |
| 0.0005 | 20.05 | 4200 | 0.0208 | 0.7816 |
| 0.0005 | 21.0 | 4400 | 0.0218 | 0.7816 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Feb 17, 2024
- Updated
- Feb 17, 2024