---
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-dt-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-uncased-english-cefr-lexical-evaluation-dt-v1

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5309
- Accuracy: 0.8716
- F1: 0.8713
- Precision: 0.8714
- Recall: 0.8716

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6225        | 1.0   | 3403  | 0.6408          | 0.7578   | 0.7538 | 0.7826    | 0.7578 |
| 0.3645        | 2.0   | 6806  | 0.4180          | 0.8597   | 0.8573 | 0.8554    | 0.8597 |
| 0.2349        | 3.0   | 10209 | 0.4452          | 0.8631   | 0.8621 | 0.8637    | 0.8631 |
| 0.1269        | 4.0   | 13612 | 0.5257          | 0.8694   | 0.8690 | 0.8690    | 0.8694 |
| 0.0605        | 5.0   | 17015 | 0.6865          | 0.8671   | 0.8668 | 0.8669    | 0.8671 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3