metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: nlp_til3
results: []
nlp_til3
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- 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: 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 219 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 2.0 | 438 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0312 | 3.0 | 657 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0312 | 4.0 | 876 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0004 | 5.0 | 1095 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1