---
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-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-bs-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: 1.6208
- Accuracy: 0.5876
- F1: 0.5859
- Precision: 0.5892
- Recall: 0.5876

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3819        | 1.0   | 173  | 1.3925          | 0.4859   | 0.4780 | 0.4752    | 0.4859 |
| 1.0132        | 2.0   | 346  | 1.3560          | 0.5011   | 0.5008 | 0.5815    | 0.5011 |
| 0.4879        | 3.0   | 519  | 1.4646          | 0.5510   | 0.5532 | 0.5612    | 0.5510 |
| 0.1783        | 4.0   | 692  | 1.7720          | 0.5713   | 0.5705 | 0.5724    | 0.5713 |
| 0.0539        | 5.0   | 865  | 1.9786          | 0.5634   | 0.5650 | 0.5701    | 0.5634 |


### Framework versions

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