---
base_model: microsoft/codebert-base-mlm
tags:
- generated_from_trainer
model-index:
- name: CBertbase-mlm-APPS10k
  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. -->

# CBertbase-mlm-APPS10k

This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0911

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.1352        | 0.05  | 500   | 1.8774          |
| 1.1754        | 0.1   | 1000  | 1.4835          |
| 1.4127        | 0.15  | 1500  | 1.4475          |
| 1.0497        | 0.2   | 2000  | 1.3342          |
| 1.0403        | 0.25  | 2500  | 1.2589          |
| 1.0754        | 0.3   | 3000  | 1.2174          |
| 0.8836        | 0.35  | 3500  | 1.2265          |
| 0.95          | 0.4   | 4000  | 1.1931          |
| 1.0324        | 0.45  | 4500  | 1.1729          |
| 1.0296        | 0.5   | 5000  | 1.1462          |
| 0.886         | 0.55  | 5500  | 1.1364          |
| 0.9352        | 0.6   | 6000  | 1.1201          |
| 1.0547        | 0.65  | 6500  | 1.1481          |
| 0.8277        | 0.7   | 7000  | 1.1128          |
| 0.8685        | 0.75  | 7500  | 1.1153          |
| 0.9277        | 0.8   | 8000  | 1.1194          |
| 0.8111        | 0.85  | 8500  | 1.0975          |
| 0.9345        | 0.9   | 9000  | 1.0913          |
| 0.9166        | 0.95  | 9500  | 1.0904          |
| 0.952         | 1.0   | 10000 | 1.0911          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2