distilbert-finetuned
This model is a fine-tuned version of distilbert-base-uncased on an code-text-classifier dataset. It achieves the following results on the evaluation set:
- Loss: 0.0033
- Accuracy: 1.0
- F1: 1.0
Model description
Finetuned model of distilbert for intent classification.
Intended uses & limitations
Classify Questions/User's Prompt for either code generation or text generation.
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2209 | 1.0 | 52 | 0.0111 | 1.0 | 1.0 |
| 0.0114 | 2.0 | 104 | 0.0041 | 1.0 | 1.0 |
| 0.0048 | 3.0 | 156 | 0.0033 | 1.0 | 1.0 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for JeswinMS4/distilbert-finetuned
Base model
distilbert/distilbert-base-uncased