metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my_distilbert_model
results: []
my_distilbert_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: 0.4847
- Accuracy: 0.8462
- F1: 0.8461
- Precision: 0.8464
- Recall: 0.8462
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4118 | 1.0 | 534 | 0.4174 | 0.8180 | 0.8151 | 0.8395 | 0.8180 |
| 0.2549 | 2.0 | 1068 | 0.3921 | 0.8499 | 0.8498 | 0.8509 | 0.8499 |
| 0.161 | 3.0 | 1602 | 0.4847 | 0.8462 | 0.8461 | 0.8464 | 0.8462 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1