Downloads · 30 days
6
21% of all-time downloads
liberta-large-topic_classification
izaitova/liberta-large-topic_classification
liberta-large-topic_classification is a machine learning model from izaitova. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-4.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
29
Public
Parameters
337M
1.3 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- License
- cc-by-4.0
- Model type
- bert
- Access
- Public
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024
- SHA
- 6f943252
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. -->
liberta-large-topic_classification
This model is a fine-tuned version of Goader/liberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7957
- Precision: 0.9167
- Recall: 0.8749
- F1: 0.8889
- Accuracy: 0.8971
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: 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 88 | 0.7214 | 0.8294 | 0.7438 | 0.7532 | 0.7843 |
| No log | 2.0 | 176 | 0.6388 | 0.8181 | 0.7797 | 0.7826 | 0.8088 |
| No log | 3.0 | 264 | 0.8149 | 0.8625 | 0.8692 | 0.8617 | 0.8725 |
| No log | 4.0 | 352 | 0.8210 | 0.9171 | 0.8603 | 0.8695 | 0.8824 |
| No log | 5.0 | 440 | 0.7850 | 0.9173 | 0.8700 | 0.8841 | 0.8922 |
| 0.3285 | 6.0 | 528 | 0.7936 | 0.8987 | 0.8670 | 0.8770 | 0.8824 |
| 0.3285 | 7.0 | 616 | 0.7794 | 0.9217 | 0.8749 | 0.8913 | 0.8971 |
| 0.3285 | 8.0 | 704 | 0.7835 | 0.9217 | 0.8749 | 0.8913 | 0.8971 |
| 0.3285 | 9.0 | 792 | 0.7947 | 0.9167 | 0.8749 | 0.8889 | 0.8971 |
| 0.3285 | 10.0 | 880 | 0.7957 | 0.9167 | 0.8749 | 0.8889 | 0.8971 |
Framework versions
- Transformers 4.39.3
- Pytorch 1.11.0a0+17540c5
- Datasets 2.21.0
- Tokenizers 0.15.2
- Type
- bert
- License
- cc-by-4.0
- Created
- Sep 9, 2024
- Updated
- Sep 9, 2024