metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-pos-2
results: []
distilbert-base-uncased-finetuned-pos-2
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: 0.3041
- Precision: 0.9155
- Recall: 0.9201
- F1: 0.9178
- Accuracy: 0.9292
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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.7867 | 1.0 | 878 | 0.3621 | 0.8983 | 0.9061 | 0.9022 | 0.9177 |
| 0.245 | 2.0 | 1756 | 0.3282 | 0.9092 | 0.9104 | 0.9098 | 0.9232 |
| 0.1919 | 3.0 | 2634 | 0.3052 | 0.9122 | 0.9180 | 0.9151 | 0.9268 |
| 0.1622 | 4.0 | 3512 | 0.2982 | 0.9146 | 0.9182 | 0.9164 | 0.9280 |
| 0.1425 | 5.0 | 4390 | 0.3041 | 0.9155 | 0.9201 | 0.9178 | 0.9292 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2