---
license: bsd-3-clause
base_model: Salesforce/codet5p-220m
tags:
- generated_from_trainer
model-index:
- name: SolExplain
  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. -->

# SolExplain

This model is a fine-tuned version of [Salesforce/codet5p-220m](https://huggingface.co./Salesforce/codet5p-220m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2952

## 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: 10
- eval_batch_size: 10
- seed: 100
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 40
- total_eval_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 0.658         | 1.0   | 19184  | 0.5830          |
| 0.5403        | 2.0   | 38368  | 0.4988          |
| 0.48          | 3.0   | 57552  | 0.4473          |
| 0.4282        | 4.0   | 76736  | 0.4124          |
| 0.3918        | 5.0   | 95920  | 0.3857          |
| 0.3464        | 6.0   | 115104 | 0.3650          |
| 0.3222        | 7.0   | 134288 | 0.3503          |
| 0.3007        | 8.0   | 153472 | 0.3357          |
| 0.2782        | 9.0   | 172656 | 0.3269          |
| 0.2562        | 10.0  | 191840 | 0.3184          |
| 0.2386        | 11.0  | 211024 | 0.3101          |
| 0.2196        | 12.0  | 230208 | 0.3020          |
| 0.2042        | 13.0  | 249392 | 0.3005          |
| 0.1931        | 14.0  | 268576 | 0.2971          |
| 0.1734        | 15.0  | 287760 | 0.2952          |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3