---
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-v6
  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-v6

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: 1.4919
- Accuracy: 0.7204
- F1: 0.7215
- Precision: 0.7239
- Recall: 0.7204

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.9855        | 1.0   | 937  | 1.0026          | 0.6225   | 0.6227 | 0.6604    | 0.6225 |
| 0.6191        | 2.0   | 1874 | 0.8113          | 0.7090   | 0.7056 | 0.7160    | 0.7090 |
| 0.2736        | 3.0   | 2811 | 0.9598          | 0.7084   | 0.7070 | 0.7099    | 0.7084 |
| 0.1399        | 4.0   | 3748 | 1.2784          | 0.7130   | 0.7126 | 0.7151    | 0.7130 |
| 0.0521        | 5.0   | 4685 | 1.5455          | 0.7152   | 0.7163 | 0.7182    | 0.7152 |


### Framework versions

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