README.md

---
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-ep-v3
  results: []
---

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# distilbert-base-uncased-english-cefr-lexical-evaluation-ep-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: 1.6313
- Accuracy: 0.6020
- F1: 0.6038
- Precision: 0.6142
- Recall: 0.6020

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3952        | 1.0   | 346  | 1.4844          | 0.4345   | 0.4087 | 0.4461    | 0.4345 |
| 1.0574        | 2.0   | 692  | 1.2710          | 0.5322   | 0.5369 | 0.5575    | 0.5322 |
| 0.438         | 3.0   | 1038 | 1.4605          | 0.5590   | 0.5593 | 0.5751    | 0.5590 |
| 0.0248        | 4.0   | 1384 | 1.8197          | 0.5720   | 0.5735 | 0.5801    | 0.5720 |


### Framework versions

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