Downloads · 30 days
12
4% of all-time downloads
esm2_t12_35M_UR50D-finetuned-localization
Robayet2023/esm2_t12_35M_UR50D-finetuned-localization
esm2_t12_35M_UR50D-finetuned-localization is a text classification model from Robayet2023. 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
330
Public
Repo size
272 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin136 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- esm
- Access
- Public
- Created
- Aug 1, 2023
- Updated
- Aug 6, 2023
- SHA
- 9bc722ed
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. -->
esm2_t12_35M_UR50D-finetuned-localization
This model is a fine-tuned version of facebook/esm2_t12_35M_UR50D on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0331
- Accuracy: 0.4835
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: 10
- eval_batch_size: 10
- 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 | Accuracy |
|---|---|---|---|---|
| 0.042 | 1.0 | 23758 | 0.0388 | 0.4835 |
| 0.0325 | 2.0 | 47516 | 0.0351 | 0.4835 |
| 0.0259 | 3.0 | 71274 | 0.0331 | 0.4835 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.3
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- esm
- License
- mit
- Created
- Aug 1, 2023
- Updated
- Aug 6, 2023