|
--- |
|
license: apache-2.0 |
|
base_model: Salesforce/codet5-small |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: codet5-small-ft-v7-iter-f |
|
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-small-ft-v7-iter-f |
|
|
|
This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3579 |
|
- Rouge1: 65.1905 |
|
- Rouge2: 58.0093 |
|
- Rougel: 64.6754 |
|
- Rougelsum: 64.9444 |
|
- Gen Len: 12.7593 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 4 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| No log | 1.0 | 20 | 1.2614 | 53.6789 | 41.4991 | 53.6127 | 53.6281 | 11.9259 | |
|
| No log | 2.0 | 40 | 0.5435 | 53.3609 | 42.8943 | 50.5216 | 50.638 | 16.1852 | |
|
| No log | 3.0 | 60 | 0.3948 | 57.8859 | 48.6662 | 57.8364 | 57.7638 | 11.4815 | |
|
| No log | 4.0 | 80 | 0.3579 | 65.1905 | 58.0093 | 64.6754 | 64.9444 | 12.7593 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.0.dev0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
