---
license: apache-2.0
base_model: Pipper/SolCoder
tags:
- generated_from_trainer
model-index:
- name: SolCoder
  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. -->

# SolCoder

This model is a fine-tuned version of [Pipper/SolCoder](https://huggingface.co./Pipper/SolCoder) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5568

## 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: 37
- eval_batch_size: 37
- seed: 100
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 148
- total_eval_batch_size: 148
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 0.6094        | 1.0   | 7440   | 0.6185          |
| 0.598         | 2.0   | 14880  | 0.6124          |
| 0.5845        | 3.0   | 22320  | 0.6075          |
| 0.5723        | 4.0   | 29760  | 0.6006          |
| 0.5589        | 5.0   | 37200  | 0.5943          |
| 0.5495        | 6.0   | 44640  | 0.5894          |
| 0.5371        | 7.0   | 52080  | 0.5861          |
| 0.5291        | 8.0   | 59520  | 0.5811          |
| 0.52          | 9.0   | 66960  | 0.5765          |
| 0.5095        | 10.0  | 74400  | 0.5746          |
| 0.5056        | 11.0  | 81840  | 0.5700          |
| 0.4967        | 12.0  | 89280  | 0.5682          |
| 0.4894        | 13.0  | 96720  | 0.5659          |
| 0.4861        | 14.0  | 104160 | 0.5619          |
| 0.4773        | 15.0  | 111600 | 0.5599          |
| 0.4754        | 16.0  | 119040 | 0.5599          |
| 0.4689        | 17.0  | 126480 | 0.5578          |
| 0.4642        | 18.0  | 133920 | 0.5575          |
| 0.4627        | 19.0  | 141360 | 0.5566          |
| 0.4573        | 20.0  | 148800 | 0.5568          |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.1.0+cu121
- Datasets 2.11.0
- Tokenizers 0.13.3