metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Training_Checkpoint
results: []
Training_Checkpoint
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: 0.1068
- Accuracy: 0.971
- F1: 0.9787
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 63 | 0.3497 | 0.869 | 0.9042 |
| No log | 2.0 | 126 | 0.2406 | 0.918 | 0.9418 |
| No log | 3.0 | 189 | 0.1529 | 0.954 | 0.9665 |
| No log | 4.0 | 252 | 0.1176 | 0.966 | 0.9751 |
| No log | 5.0 | 315 | 0.1068 | 0.971 | 0.9787 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1