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-DIALOCONAN-WIKI-CLS
results: []
distilbert-base-uncased-DIALOCONAN-WIKI-CLS
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: 0.4006
- Precision: 0.6306
- Recall: 0.6327
- F1: 0.6316
- Accuracy: 0.9460
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|
| 0.3444 | 1.0 | 2500 | 0.3613 | 0.6877 | 0.6910 | 0.6884 | 0.9171 |
| 0.2104 | 2.0 | 5000 | 0.3773 | 0.7006 | 0.7035 | 0.7017 | 0.9344 |
| 0.1061 | 3.0 | 7500 | 0.3585 | 0.7054 | 0.7074 | 0.7063 | 0.9404 |
| 0.0669 | 4.0 | 10000 | 0.4002 | 0.6291 | 0.6309 | 0.6299 | 0.9434 |
| 0.0327 | 5.0 | 12500 | 0.4006 | 0.6306 | 0.6327 | 0.6316 | 0.9460 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1