---
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: []
---

<!-- 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-bs-v4

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: 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