Downloads · 30 days
11
7% of all-time downloads
N_roberta_twitterfin_padding80model
Realgon/N_roberta_twitterfin_padding80model
N_roberta_twitterfin_padding80model is a text classification model from Realgon. 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
167
Public
Repo size
10.5 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin499 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Dec 25, 2023
- Updated
- Dec 25, 2023
- SHA
- 9e669168
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. -->
N_roberta_twitterfin_padding80model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9104
- Accuracy: 0.9045
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5492 | 1.0 | 597 | 0.3187 | 0.8848 |
| 0.3028 | 2.0 | 1194 | 0.2528 | 0.9054 |
| 0.2565 | 3.0 | 1791 | 0.3721 | 0.8907 |
| 0.1877 | 4.0 | 2388 | 0.4450 | 0.8991 |
| 0.1604 | 5.0 | 2985 | 0.5126 | 0.8953 |
| 0.0864 | 6.0 | 3582 | 0.6042 | 0.8987 |
| 0.068 | 7.0 | 4179 | 0.7240 | 0.8953 |
| 0.0497 | 8.0 | 4776 | 0.7586 | 0.8991 |
| 0.0459 | 9.0 | 5373 | 0.7846 | 0.9020 |
| 0.0483 | 10.0 | 5970 | 0.7701 | 0.9008 |
| 0.0319 | 11.0 | 6567 | 0.8474 | 0.8920 |
| 0.0244 | 12.0 | 7164 | 0.7441 | 0.9054 |
| 0.022 | 13.0 | 7761 | 0.7594 | 0.9079 |
| 0.0226 | 14.0 | 8358 | 0.8739 | 0.9037 |
| 0.0165 | 15.0 | 8955 | 0.8453 | 0.9020 |
| 0.0093 | 16.0 | 9552 | 0.8394 | 0.9020 |
| 0.0092 | 17.0 | 10149 | 0.8803 | 0.9054 |
| 0.0088 | 18.0 | 10746 | 0.9146 | 0.9045 |
| 0.0028 | 19.0 | 11343 | 0.9085 | 0.9020 |
| 0.0034 | 20.0 | 11940 | 0.9104 | 0.9045 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 25, 2023
- Updated
- Dec 25, 2023