---
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-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-dt-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: 0.5788
- Accuracy: 0.8580
- F1: 0.8573
- Precision: 0.8576
- Recall: 0.8580

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6508        | 1.0   | 3527  | 0.6211          | 0.7680   | 0.7675 | 0.7789    | 0.7680 |
| 0.4088        | 2.0   | 7054  | 0.4281          | 0.8562   | 0.8549 | 0.8574    | 0.8562 |
| 0.2476        | 3.0   | 10581 | 0.4526          | 0.8577   | 0.8570 | 0.8574    | 0.8577 |
| 0.1298        | 4.0   | 14108 | 0.5618          | 0.8638   | 0.8630 | 0.8635    | 0.8638 |
| 0.0615        | 5.0   | 17635 | 0.6939          | 0.8632   | 0.8629 | 0.8629    | 0.8632 |


### Framework versions

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