metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: sentence-classifiert
results: []
sentence-classifiert
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: 0.6252
- Precision: 0.7535
- Recall: 0.7518
- Accuracy: 0.7518
- F1: 0.7521
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: 32
- eval_batch_size: 32
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 154 | 0.9047 | 0.6004 | 0.5895 | 0.5858 | 0.5781 |
| No log | 2.0 | 308 | 0.7097 | 0.6792 | 0.6805 | 0.6802 | 0.6711 |
| No log | 3.0 | 462 | 0.6422 | 0.7320 | 0.7322 | 0.7315 | 0.7266 |
| 0.773 | 4.0 | 616 | 0.6549 | 0.7433 | 0.7373 | 0.7364 | 0.7372 |
| 0.773 | 5.0 | 770 | 0.6252 | 0.7535 | 0.7518 | 0.7518 | 0.7521 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2