metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: test_trainer
results: []
test_trainer
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: 0.5486
- Accuracy: 0.9374
- F1: 0.5984
- Precision: 0.7067
- Recall: 0.5189
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.6604 | 1.0 | 9009 | 0.6454 | 0.9258 | 0.3847 | 0.7537 | 0.2583 |
| 0.5947 | 2.0 | 18018 | 0.4696 | 0.9356 | 0.6004 | 0.6779 | 0.5387 |
| 0.5444 | 3.0 | 27027 | 0.5486 | 0.9374 | 0.5984 | 0.7067 | 0.5189 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1