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---
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
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