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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-bs-v3
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-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: 1.8231
- Accuracy: 0.6266
- F1: 0.6262
- Precision: 0.6333
- Recall: 0.6266
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.2788 | 1.0 | 346 | 1.3442 | 0.4996 | 0.4895 | 0.5071 | 0.4996 |
| 1.0093 | 2.0 | 692 | 1.2521 | 0.5670 | 0.5689 | 0.5959 | 0.5670 |
| 0.5086 | 3.0 | 1038 | 1.4732 | 0.5902 | 0.5918 | 0.5978 | 0.5902 |
| 0.2153 | 4.0 | 1384 | 1.9881 | 0.6010 | 0.6016 | 0.6120 | 0.6010 |
| 0.0496 | 5.0 | 1730 | 2.0705 | 0.6003 | 0.6015 | 0.6047 | 0.6003 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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