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

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.4626        | 0.05  | 500   | 0.0390          |
| 0.0215        | 0.1   | 1000  | 0.0065          |
| 0.0096        | 0.15  | 1500  | 0.0018          |
| 0.0022        | 0.2   | 2000  | 0.0009          |
| 0.0023        | 0.25  | 2500  | 0.0003          |
| 0.0011        | 0.3   | 3000  | 0.0004          |
| 0.0011        | 0.35  | 3500  | 0.0002          |
| 0.0016        | 0.4   | 4000  | 0.0002          |
| 0.0006        | 0.45  | 4500  | 0.0001          |
| 0.0004        | 0.5   | 5000  | 0.0001          |
| 0.0002        | 0.55  | 5500  | 0.0001          |
| 0.0002        | 0.6   | 6000  | 0.0001          |
| 0.0003        | 0.65  | 6500  | 0.0001          |
| 0.0001        | 0.7   | 7000  | 0.0001          |
| 0.0001        | 0.75  | 7500  | 0.0001          |
| 0.0001        | 0.8   | 8000  | 0.0001          |
| 0.0001        | 0.85  | 8500  | 0.0001          |
| 0.0001        | 0.9   | 9000  | 0.0001          |
| 0.0001        | 0.95  | 9500  | 0.0001          |
| 0.0001        | 1.0   | 10000 | 0.0001          |


### Framework versions

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