---
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-v1
  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-v1

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: 1.1930
- Accuracy: 0.5941
- F1: 0.5907
- Precision: 0.5913
- Recall: 0.5941

## 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: 64
- eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 44   | 1.4290          | 0.4439   | 0.3994 | 0.4597    | 0.4439 |
| 1.5279        | 2.0   | 88   | 1.2962          | 0.5076   | 0.4992 | 0.5300    | 0.5076 |
| 1.0713        | 3.0   | 132  | 1.2973          | 0.5293   | 0.5328 | 0.5564    | 0.5293 |
| 0.624         | 4.0   | 176  | 1.3405          | 0.5583   | 0.5550 | 0.5559    | 0.5583 |
| 0.3372        | 5.0   | 220  | 1.3920          | 0.5424   | 0.5445 | 0.5515    | 0.5424 |


### Framework versions

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