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

# SolCoderFuncs

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: 0.5574

## 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: 40

### Training results

| Training Loss | Epoch | Step   | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 0.8793        | 1.0   | 3600   | 0.7881          |
| 0.7622        | 2.0   | 7200   | 0.7190          |
| 0.7077        | 3.0   | 10800  | 0.6769          |
| 0.659         | 4.0   | 14400  | 0.6518          |
| 0.6212        | 5.0   | 18000  | 0.6300          |
| 0.589         | 6.0   | 21600  | 0.6119          |
| 0.562         | 7.0   | 25200  | 0.6014          |
| 0.5361        | 8.0   | 28800  | 0.5905          |
| 0.5171        | 9.0   | 32400  | 0.5799          |
| 0.4973        | 10.0  | 36000  | 0.5747          |
| 0.4772        | 11.0  | 39600  | 0.5666          |
| 0.4619        | 12.0  | 43200  | 0.5610          |
| 0.4443        | 13.0  | 46800  | 0.5588          |
| 0.4335        | 14.0  | 50400  | 0.5571          |
| 0.4192        | 15.0  | 54000  | 0.5534          |
| 0.4062        | 16.0  | 57600  | 0.5512          |
| 0.3977        | 17.0  | 61200  | 0.5513          |
| 0.3864        | 18.0  | 64800  | 0.5515          |
| 0.3791        | 19.0  | 68400  | 0.5507          |
| 0.3718        | 20.0  | 72000  | 0.5510          |
| 0.4132        | 21.0  | 75600  | 0.5551          |
| 0.4079        | 22.0  | 79200  | 0.5499          |
| 0.3957        | 23.0  | 82800  | 0.5522          |
| 0.3895        | 24.0  | 86400  | 0.5482          |
| 0.3797        | 25.0  | 90000  | 0.5477          |
| 0.3686        | 26.0  | 93600  | 0.5486          |
| 0.3628        | 27.0  | 97200  | 0.5491          |
| 0.3518        | 28.0  | 100800 | 0.5502          |
| 0.3452        | 29.0  | 104400 | 0.5494          |
| 0.3379        | 30.0  | 108000 | 0.5546          |
| 0.3292        | 31.0  | 111600 | 0.5486          |
| 0.3232        | 32.0  | 115200 | 0.5522          |
| 0.3146        | 33.0  | 118800 | 0.5524          |
| 0.31          | 34.0  | 122400 | 0.5505          |
| 0.3057        | 35.0  | 126000 | 0.5538          |
| 0.301         | 36.0  | 129600 | 0.5549          |
| 0.2955        | 37.0  | 133200 | 0.5557          |
| 0.2901        | 38.0  | 136800 | 0.5554          |
| 0.2872        | 39.0  | 140400 | 0.5564          |
| 0.2844        | 40.0  | 144000 | 0.5574          |


### Framework versions

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