metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: results
results: []
results
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0107
- Model Preparation Time: 0.0007
- F1: 0.9970
- Precision: 0.9971
- Recall: 0.9970
- Accuracy: 0.9970
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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|---|
| 0.0166 | 0.3367 | 100 | 0.0102 | 0.0007 | 0.9979 | 0.9979 | 0.9979 | 0.9979 |
| 0.0022 | 0.6734 | 200 | 0.0052 | 0.0007 | 0.9983 | 0.9983 | 0.9983 | 0.9983 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 3.0.1
- Tokenizers 0.20.1