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-ep-v3
results: []
distilbert-base-uncased-english-cefr-lexical-evaluation-ep-v3
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: 1.6313
- Accuracy: 0.6020
- F1: 0.6038
- Precision: 0.6142
- Recall: 0.6020
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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.3952 | 1.0 | 346 | 1.4844 | 0.4345 | 0.4087 | 0.4461 | 0.4345 |
| 1.0574 | 2.0 | 692 | 1.2710 | 0.5322 | 0.5369 | 0.5575 | 0.5322 |
| 0.438 | 3.0 | 1038 | 1.4605 | 0.5590 | 0.5593 | 0.5751 | 0.5590 |
| 0.0248 | 4.0 | 1384 | 1.8197 | 0.5720 | 0.5735 | 0.5801 | 0.5720 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3