Downloads · 30 days
83
21% of all-time downloads
distilroberta-base-finetuned-wikitext2
serene89104/distilroberta-base-finetuned-wikitext2
distilroberta-base-finetuned-wikitext2 is a fill-mask model from serene89104. Use it when you need the model to fill a missing word. 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
396
Public
Parameters
82.2M
47.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors329 MB · 100%
At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Mar 31, 2024
- Updated
- Apr 8, 2024
- SHA
- dbef6f2c
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. -->
distilroberta-base-finetuned-wikitext2
This model is a fine-tuned version of distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2131
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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5524 | 1.0 | 21105 | 1.3548 |
| 1.4257 | 2.0 | 42210 | 1.2585 |
| 1.3838 | 3.0 | 63315 | 1.2192 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Mar 31, 2024
- Updated
- Apr 8, 2024