Downloads · 30 days
5
45% of all-time downloads
distilbert-base-uncased-lora-text-classification
kerier/distilbert-base-uncased-lora-text-classification
distilbert-base-uncased-lora-text-classification is a machine learning model from kerier. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
11
Public
Repo size
4.8 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.4 MB · 71%
At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Sep 18, 2024
- Updated
- Sep 18, 2024
- SHA
- dd2000a1
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. -->
distilbert-base-uncased-lora-text-classification
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7922
- Accuracy: {'accuracy': 0.88}
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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 250 | 0.3212 | {'accuracy': 0.862} |
| 0.4694 | 2.0 | 500 | 0.3175 | {'accuracy': 0.89} |
| 0.4694 | 3.0 | 750 | 0.4655 | {'accuracy': 0.872} |
| 0.3081 | 4.0 | 1000 | 0.5394 | {'accuracy': 0.885} |
| 0.3081 | 5.0 | 1250 | 0.6248 | {'accuracy': 0.871} |
| 0.1875 | 6.0 | 1500 | 0.7691 | {'accuracy': 0.877} |
| 0.1875 | 7.0 | 1750 | 0.6730 | {'accuracy': 0.884} |
| 0.1041 | 8.0 | 2000 | 0.6989 | {'accuracy': 0.882} |
| 0.1041 | 9.0 | 2250 | 0.7978 | {'accuracy': 0.879} |
| 0.0363 | 10.0 | 2500 | 0.7922 | {'accuracy': 0.88} |
Framework versions
- PEFT 0.11.1
- Transformers 4.37.0
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.15.2
- Library
- peft
- License
- apache-2.0
- Created
- Sep 18, 2024
- Updated
- Sep 18, 2024