---
base_model: microsoft/codebert-base-mlm
tags:
- generated_from_trainer
model-index:
- name: huggingfacecodebert-base-mlm-finetuned-st
  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. -->

# huggingfacecodebert-base-mlm-finetuned-st

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: 0.9298

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.761         | 0.05  | 500   | 1.6477          |
| 1.2184        | 0.1   | 1000  | 1.2377          |
| 0.9962        | 0.15  | 1500  | 1.1013          |
| 0.026         | 0.2   | 2000  | 1.0762          |
| 0.0266        | 0.25  | 2500  | 1.0639          |
| 0.6503        | 0.3   | 3000  | 0.9464          |
| 0.382         | 0.35  | 3500  | 0.9406          |
| 0.6019        | 0.4   | 4000  | 0.9027          |
| 0.39          | 0.45  | 4500  | 0.8842          |
| 0.0243        | 0.5   | 5000  | 0.9107          |
| 0.0238        | 0.55  | 5500  | 0.9165          |
| 0.205         | 0.6   | 6000  | 0.9304          |
| 0.4026        | 0.65  | 6500  | 0.9098          |
| 0.334         | 0.7   | 7000  | 0.9271          |
| 0.2539        | 0.75  | 7500  | 0.9402          |
| 0.1819        | 0.8   | 8000  | 0.9272          |
| 0.5093        | 0.85  | 8500  | 0.9314          |
| 0.0882        | 0.9   | 9000  | 0.9259          |
| 0.3341        | 0.95  | 9500  | 0.9275          |
| 0.0233        | 1.0   | 10000 | 0.9298          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0