metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert_finetune_own_data_model
results: []
distilbert_finetune_own_data_model
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: 0.0015
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
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: 5e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 5 | 0.3747 | 1.0 | 0.25 | 0.4 | 0.76 |
| No log | 2.0 | 10 | 0.1132 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 3.0 | 15 | 0.0180 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 4.0 | 20 | 0.0054 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 5.0 | 25 | 0.0028 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 6.0 | 30 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 7.0 | 35 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 8.0 | 40 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 9.0 | 45 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 10.0 | 50 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2