metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: distilbert-base-multilingual-cased
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: multilabel_lora_distilbert_runews_classifier_tuned
results: []
multilabel_lora_distilbert_runews_classifier_tuned
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0019
- Accuracy: 0.8276
- F1: 0.8284
- Precision: 0.8317
- Recall: 0.8276
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: 0.0009143508688456378
- 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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 91 | 0.5987 | 0.7634 | 0.7621 | 0.7648 | 0.7634 |
| No log | 2.0 | 182 | 0.3768 | 0.8693 | 0.8698 | 0.8767 | 0.8693 |
| No log | 3.0 | 273 | 0.2620 | 0.9065 | 0.9063 | 0.9093 | 0.9065 |
| No log | 4.0 | 364 | 0.2427 | 0.9202 | 0.9203 | 0.9220 | 0.9202 |
| No log | 5.0 | 455 | 0.2244 | 0.9367 | 0.9369 | 0.9387 | 0.9367 |
| 0.3641 | 6.0 | 546 | 0.2385 | 0.9491 | 0.9491 | 0.9495 | 0.9491 |
| 0.3641 | 7.0 | 637 | 0.2560 | 0.9464 | 0.9464 | 0.9465 | 0.9464 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1