---
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-dp-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-dp-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: 1.4726
- Accuracy: 0.5877
- F1: 0.5893
- Precision: 0.5974
- Recall: 0.5877

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.5441        | 1.0   | 139  | 1.2777          | 0.5136   | 0.5044 | 0.5164    | 0.5136 |
| 1.1611        | 2.0   | 278  | 1.1085          | 0.6058   | 0.5976 | 0.6336    | 0.6058 |
| 0.4865        | 3.0   | 417  | 1.2582          | 0.6058   | 0.6045 | 0.6216    | 0.6058 |
| 0.2134        | 4.0   | 556  | 1.4254          | 0.6239   | 0.6261 | 0.6295    | 0.6239 |
| 0.1313        | 5.0   | 695  | 1.5587          | 0.6239   | 0.6251 | 0.6277    | 0.6239 |


### Framework versions

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