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-v1
results: []
distilbert-base-uncased-english-cefr-lexical-evaluation-bs-v1
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: 1.1930
- Accuracy: 0.5941
- F1: 0.5907
- Precision: 0.5913
- Recall: 0.5941
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: 64
- eval_batch_size: 64
- 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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 44 | 1.4290 | 0.4439 | 0.3994 | 0.4597 | 0.4439 |
| 1.5279 | 2.0 | 88 | 1.2962 | 0.5076 | 0.4992 | 0.5300 | 0.5076 |
| 1.0713 | 3.0 | 132 | 1.2973 | 0.5293 | 0.5328 | 0.5564 | 0.5293 |
| 0.624 | 4.0 | 176 | 1.3405 | 0.5583 | 0.5550 | 0.5559 | 0.5583 |
| 0.3372 | 5.0 | 220 | 1.3920 | 0.5424 | 0.5445 | 0.5515 | 0.5424 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3