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---
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-v4
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-v4
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: 0.5788
- Accuracy: 0.8580
- F1: 0.8573
- Precision: 0.8576
- Recall: 0.8580
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6508 | 1.0 | 3527 | 0.6211 | 0.7680 | 0.7675 | 0.7789 | 0.7680 |
| 0.4088 | 2.0 | 7054 | 0.4281 | 0.8562 | 0.8549 | 0.8574 | 0.8562 |
| 0.2476 | 3.0 | 10581 | 0.4526 | 0.8577 | 0.8570 | 0.8574 | 0.8577 |
| 0.1298 | 4.0 | 14108 | 0.5618 | 0.8638 | 0.8630 | 0.8635 | 0.8638 |
| 0.0615 | 5.0 | 17635 | 0.6939 | 0.8632 | 0.8629 | 0.8629 | 0.8632 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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