---
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-v2
  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-v2

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: 1.2611
- Accuracy: 0.5899
- F1: 0.5891
- Precision: 0.5980
- Recall: 0.5899

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.5468        | 1.0   | 121  | 1.2644          | 0.5042   | 0.4882 | 0.5160    | 0.5042 |
| 1.104         | 2.0   | 242  | 1.1827          | 0.5657   | 0.5662 | 0.5870    | 0.5657 |
| 0.6801        | 3.0   | 363  | 1.2386          | 0.5850   | 0.5791 | 0.5858    | 0.5850 |
| 0.3537        | 4.0   | 484  | 1.4693          | 0.5742   | 0.5733 | 0.5763    | 0.5742 |
| 0.0661        | 5.0   | 605  | 1.6088          | 0.5850   | 0.5857 | 0.5874    | 0.5850 |


### Framework versions

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