---
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-v5
  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-v5

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: 1.6329
- Accuracy: 0.6599
- F1: 0.6615
- Precision: 0.6649
- Recall: 0.6599

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.1732        | 1.0   | 367  | 1.0065          | 0.6292   | 0.6249 | 0.6360    | 0.6292 |
| 0.7751        | 2.0   | 734  | 0.9342          | 0.6649   | 0.6630 | 0.6629    | 0.6649 |
| 0.3269        | 3.0   | 1101 | 1.1524          | 0.6483   | 0.6491 | 0.6634    | 0.6483 |
| 0.1226        | 4.0   | 1468 | 1.4517          | 0.6558   | 0.6573 | 0.6594    | 0.6558 |
| 0.0599        | 5.0   | 1835 | 1.6189          | 0.6697   | 0.6715 | 0.6753    | 0.6697 |


### Framework versions

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