File size: 2,841 Bytes
1b764dd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: t5-small-codesearchnet-multilang-python-java
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. -->
# t5-small-codesearchnet-multilang-python-java
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7015
- Bleu: 0.0045
- Rouge1: 0.2194
- Rouge2: 0.0741
- Avg Length: 15.9976
## 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: 10
- total_train_batch_size: 80
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Avg Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:----------:|
| No log | 1.0 | 375 | 0.9005 | 0.0013 | 0.1397 | 0.0334 | 16.3976 |
| 2.3568 | 2.0 | 750 | 0.8036 | 0.0023 | 0.1737 | 0.0526 | 15.8896 |
| 0.7576 | 3.0 | 1125 | 0.7584 | 0.0021 | 0.1856 | 0.0558 | 15.3102 |
| 0.6778 | 4.0 | 1500 | 0.7298 | 0.0024 | 0.1922 | 0.0597 | 15.3544 |
| 0.6778 | 5.0 | 1875 | 0.7114 | 0.0037 | 0.2114 | 0.0704 | 15.7588 |
| 0.6206 | 6.0 | 2250 | 0.6949 | 0.0039 | 0.2093 | 0.0729 | 15.8088 |
| 0.5856 | 7.0 | 2625 | 0.6927 | 0.0042 | 0.2143 | 0.0711 | 16.5838 |
| 0.5447 | 8.0 | 3000 | 0.6867 | 0.005 | 0.2151 | 0.0717 | 17.2174 |
| 0.5447 | 9.0 | 3375 | 0.6895 | 0.0043 | 0.2179 | 0.0736 | 16.1068 |
| 0.5117 | 10.0 | 3750 | 0.6876 | 0.0038 | 0.2229 | 0.0777 | 15.5094 |
| 0.4892 | 11.0 | 4125 | 0.6800 | 0.0047 | 0.2201 | 0.0783 | 16.6902 |
| 0.4629 | 12.0 | 4500 | 0.6903 | 0.0047 | 0.2203 | 0.0771 | 16.7658 |
| 0.4629 | 13.0 | 4875 | 0.6947 | 0.0056 | 0.227 | 0.0777 | 16.8108 |
| 0.4355 | 14.0 | 5250 | 0.6999 | 0.0027 | 0.2028 | 0.0715 | 15.6776 |
| 0.418 | 15.0 | 5625 | 0.7015 | 0.0045 | 0.2194 | 0.0741 | 15.9976 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|