metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetune
results: []
distilbert-base-uncased-finetune
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: 0.0149
- Precision: 0.8458
- Recall: 0.8060
- F1: 0.8255
- Accuracy: 0.9954
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: 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 48 | 0.0556 | 0.5372 | 0.1902 | 0.2809 | 0.9838 |
| No log | 2.0 | 96 | 0.0171 | 0.8320 | 0.8023 | 0.8169 | 0.9951 |
| No log | 3.0 | 144 | 0.0149 | 0.8458 | 0.8060 | 0.8255 | 0.9954 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1