metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert-base-uncased
metrics:
- accuracy
model-index:
- name: multilabel_classification
results: []
multilabel_classification
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: 0.2725
- F1 Micro: 0.6677
- F1 Macro: 0.6644
- F1 Weighted: 0.6651
- Accuracy: 0.5900
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: 0.0001
- 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 | F1 Micro | F1 Macro | F1 Weighted | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 406 | 0.3793 | 0.0637 | 0.0619 | 0.0621 | 0.1413 |
| 0.4136 | 2.0 | 812 | 0.2789 | 0.6272 | 0.6225 | 0.6236 | 0.5346 |
| 0.2499 | 3.0 | 1218 | 0.2725 | 0.6677 | 0.6644 | 0.6651 | 0.5900 |
| 0.2017 | 4.0 | 1624 | 0.2744 | 0.675 | 0.6716 | 0.6721 | 0.6066 |
| 0.1853 | 5.0 | 2030 | 0.2745 | 0.6833 | 0.6797 | 0.6805 | 0.6122 |
| 0.1853 | 6.0 | 2436 | 0.2771 | 0.6781 | 0.6764 | 0.6770 | 0.6177 |
| 0.1621 | 7.0 | 2842 | 0.2810 | 0.6980 | 0.6962 | 0.6970 | 0.6343 |
| 0.1536 | 8.0 | 3248 | 0.2832 | 0.6998 | 0.6982 | 0.6988 | 0.6427 |
| 0.1414 | 9.0 | 3654 | 0.2843 | 0.6958 | 0.6943 | 0.6948 | 0.6371 |
| 0.1429 | 10.0 | 4060 | 0.2861 | 0.6928 | 0.6905 | 0.6911 | 0.6316 |
Framework versions
- PEFT 0.11.1
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.15.1