Downloads · 30 days
4
8% of all-time downloads
xlm-roberta-base-finetuned-panx-all
seobak/xlm-roberta-base-finetuned-panx-all
xlm-roberta-base-finetuned-panx-all is a token classification model from seobak. Use it when you need labels on individual words, such as names. 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
50
Public
Parameters
277M
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
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jan 15, 2024
- Updated
- Jan 15, 2024
- SHA
- 11ad9fdb
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-finetuned-panx-all
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1737
- F1: 0.8545
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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.2953 | 1.0 | 835 | 0.2001 | 0.8127 |
| 0.1564 | 2.0 | 1670 | 0.1720 | 0.8455 |
| 0.1037 | 3.0 | 2505 | 0.1737 | 0.8545 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jan 15, 2024
- Updated
- Jan 15, 2024