metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my_awesome_model
results: []
my_awesome_model
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: 0.4173
- Accuracy: 0.8465
- F1: 0.8134
- Precision: 0.8095
- Recall: 0.8173
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4196 | 1.17 | 500 | 0.4173 | 0.8465 | 0.8134 | 0.8095 | 0.8173 |
| 0.3043 | 2.33 | 1000 | 0.4959 | 0.8451 | 0.8145 | 0.7994 | 0.8301 |
| 0.2367 | 3.5 | 1500 | 0.6724 | 0.8163 | 0.7917 | 0.7389 | 0.8526 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1