---
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-v3
  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-v3

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: 1.8231
- Accuracy: 0.6266
- F1: 0.6262
- Precision: 0.6333
- Recall: 0.6266

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.2788        | 1.0   | 346  | 1.3442          | 0.4996   | 0.4895 | 0.5071    | 0.4996 |
| 1.0093        | 2.0   | 692  | 1.2521          | 0.5670   | 0.5689 | 0.5959    | 0.5670 |
| 0.5086        | 3.0   | 1038 | 1.4732          | 0.5902   | 0.5918 | 0.5978    | 0.5902 |
| 0.2153        | 4.0   | 1384 | 1.9881          | 0.6010   | 0.6016 | 0.6120    | 0.6010 |
| 0.0496        | 5.0   | 1730 | 2.0705          | 0.6003   | 0.6015 | 0.6047    | 0.6003 |


### Framework versions

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