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-v4
results: []
distilbert-base-uncased-english-cefr-lexical-evaluation-bs-v4
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: 2.1613
- Accuracy: 0.6006
- F1: 0.6030
- Precision: 0.6104
- Recall: 0.6006
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|
| 1.4569 | 1.0 | 691 | 1.4527 | 0.4388 | 0.4009 | 0.4841 | 0.4388 |
| 1.098 | 2.0 | 1382 | 1.3605 | 0.5402 | 0.5447 | 0.5679 | 0.5402 |
| 0.74 | 3.0 | 2073 | 1.8285 | 0.5532 | 0.5582 | 0.5807 | 0.5532 |
| 0.3963 | 4.0 | 2764 | 2.2860 | 0.5655 | 0.5663 | 0.5904 | 0.5655 |
| 0.1291 | 5.0 | 3455 | 2.3329 | 0.5880 | 0.5903 | 0.5956 | 0.5880 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3