---
library_name: transformers
license: apache-2.0
base_model: Salesforce/codet5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: daffa-ai-coder-multilang
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# daffa-ai-coder-multilang

This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3432
- Rouge1: 0.2895
- Rouge2: 0.1303
- Rougel: 0.2577
- Rougelsum: 0.2894

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 0.9474 | 9    | 5.2760          | 0.0941 | 0.0081 | 0.083  | 0.0886    |
| 7.4467        | 2.0    | 19   | 3.7845          | 0.1181 | 0.0207 | 0.1061 | 0.1144    |
| 4.8513        | 2.9474 | 28   | 3.1986          | 0.1836 | 0.0273 | 0.1569 | 0.1769    |
| 3.9428        | 4.0    | 38   | 2.7966          | 0.1598 | 0.0323 | 0.1541 | 0.157     |
| 3.2332        | 4.9474 | 47   | 2.5789          | 0.1775 | 0.0659 | 0.1704 | 0.1758    |
| 2.9824        | 6.0    | 57   | 2.4343          | 0.2153 | 0.0868 | 0.2064 | 0.2142    |
| 2.7661        | 6.9474 | 66   | 2.3556          | 0.2678 | 0.1189 | 0.2583 | 0.2706    |
| 2.6326        | 7.5789 | 72   | 2.3432          | 0.2895 | 0.1303 | 0.2577 | 0.2894    |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.20.3