---
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-lr-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-lr-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: 1.6545
- Accuracy: 0.2858
- F1: 0.1724
- Precision: 0.1930
- Recall: 0.2858

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.6298        | 1.0   | 87   | 1.6693          | 0.2802   | 0.1665 | 0.1883    | 0.2802 |
| 1.7023        | 2.0   | 174  | 1.7559          | 0.2194   | 0.1104 | 0.0765    | 0.2194 |
| 1.732         | 3.0   | 261  | 1.7641          | 0.1731   | 0.0861 | 0.0702    | 0.1731 |
| 1.7384        | 4.0   | 348  | 1.7511          | 0.2201   | 0.1064 | 0.0776    | 0.2201 |
| 1.7189        | 5.0   | 435  | 1.7466          | 0.2259   | 0.1101 | 0.0786    | 0.2259 |


### Framework versions

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