---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-base-uncased-finetuned-CEFR
  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-finetuned-CEFR

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2528
- Accuracy: 0.3350
- Precision: 0.3202
- Recall: 0.6791
- F1: 0.2925

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 50   | 0.2342          | 0.3324   | 0.3240    | 0.6540 | 0.2960 |
| No log        | 2.0   | 100  | 0.2326          | 0.3330   | 0.3166    | 0.6658 | 0.2841 |
| No log        | 3.0   | 150  | 0.2362          | 0.3332   | 0.3171    | 0.6680 | 0.2882 |
| No log        | 4.0   | 200  | 0.2410          | 0.3335   | 0.3238    | 0.6722 | 0.2979 |
| No log        | 5.0   | 250  | 0.2468          | 0.3337   | 0.3254    | 0.6657 | 0.2964 |
| No log        | 6.0   | 300  | 0.2455          | 0.3341   | 0.3190    | 0.6697 | 0.2937 |
| No log        | 7.0   | 350  | 0.2404          | 0.3347   | 0.3226    | 0.6795 | 0.2931 |
| No log        | 8.0   | 400  | 0.2491          | 0.3341   | 0.3298    | 0.6732 | 0.2998 |
| No log        | 9.0   | 450  | 0.2489          | 0.3345   | 0.3213    | 0.6763 | 0.2949 |
| 0.0385        | 10.0  | 500  | 0.2487          | 0.3349   | 0.3173    | 0.6780 | 0.2876 |
| 0.0385        | 11.0  | 550  | 0.2570          | 0.3346   | 0.3264    | 0.6754 | 0.2971 |
| 0.0385        | 12.0  | 600  | 0.2548          | 0.3348   | 0.3234    | 0.6746 | 0.2946 |
| 0.0385        | 13.0  | 650  | 0.2533          | 0.3349   | 0.3219    | 0.6806 | 0.2942 |
| 0.0385        | 14.0  | 700  | 0.2523          | 0.3350   | 0.3198    | 0.6801 | 0.2919 |
| 0.0385        | 15.0  | 750  | 0.2528          | 0.3350   | 0.3202    | 0.6791 | 0.2925 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1