metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilbert-base-uncased-english-cefr-lexical-evaluation-bs-v2
results: []
distilbert-base-uncased-english-cefr-lexical-evaluation-bs-v2
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: 1.6208
- Accuracy: 0.5876
- F1: 0.5859
- Precision: 0.5892
- Recall: 0.5876
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.3819 | 1.0 | 173 | 1.3925 | 0.4859 | 0.4780 | 0.4752 | 0.4859 |
| 1.0132 | 2.0 | 346 | 1.3560 | 0.5011 | 0.5008 | 0.5815 | 0.5011 |
| 0.4879 | 3.0 | 519 | 1.4646 | 0.5510 | 0.5532 | 0.5612 | 0.5510 |
| 0.1783 | 4.0 | 692 | 1.7720 | 0.5713 | 0.5705 | 0.5724 | 0.5713 |
| 0.0539 | 5.0 | 865 | 1.9786 | 0.5634 | 0.5650 | 0.5701 | 0.5634 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3