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---
library_name: transformers
license: apache-2.0
base_model: Salesforce/codet5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: CodeT5-KeyPhrases-Filtered-Valid-Phase1
  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. -->

# CodeT5-KeyPhrases-Filtered-Valid-Phase1

This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5395
- Rouge1: 0.3357
- Rouge2: 0.1004
- Rougel: 0.3230

## 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: 14
- eval_batch_size: 4
- seed: 42
- 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
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 1.2932        | 1.0   | 8    | 0.8983          | 0.2450 | 0.0317 | 0.2338 |
| 0.7191        | 2.0   | 16   | 0.7307          | 0.3123 | 0.0742 | 0.3011 |
| 0.812         | 3.0   | 24   | 0.6878          | 0.3304 | 0.0994 | 0.3186 |
| 0.4139        | 4.0   | 32   | 0.6456          | 0.3431 | 0.1057 | 0.3313 |
| 0.482         | 5.0   | 40   | 0.6134          | 0.3445 | 0.0942 | 0.3327 |
| 0.3675        | 6.0   | 48   | 0.5809          | 0.3318 | 0.0924 | 0.3210 |
| 0.4833        | 7.0   | 56   | 0.5530          | 0.3408 | 0.0963 | 0.3282 |
| 0.3695        | 8.0   | 64   | 0.5395          | 0.3357 | 0.1004 | 0.3230 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1