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-lr-v2
results: []
distilbert-base-uncased-english-cefr-lexical-evaluation-lr-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: 1.6545
- Accuracy: 0.2858
- F1: 0.1724
- Precision: 0.1930
- Recall: 0.2858
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: 0.001
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.6298 | 1.0 | 87 | 1.6693 | 0.2802 | 0.1665 | 0.1883 | 0.2802 |
| 1.7023 | 2.0 | 174 | 1.7559 | 0.2194 | 0.1104 | 0.0765 | 0.2194 |
| 1.732 | 3.0 | 261 | 1.7641 | 0.1731 | 0.0861 | 0.0702 | 0.1731 |
| 1.7384 | 4.0 | 348 | 1.7511 | 0.2201 | 0.1064 | 0.0776 | 0.2201 |
| 1.7189 | 5.0 | 435 | 1.7466 | 0.2259 | 0.1101 | 0.0786 | 0.2259 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3