metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: t5-small-codesearchnet-python
results: []
t5-small-codesearchnet-python
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0785
- Bleu: 0.035
- Rouge1: 0.6257
- Rouge2: 0.6078
- Avg Length: 16.9954
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 | 0.0801 | 0.0358 | 0.6174 | 0.6 | 17.1074 |
1.6066 | 2.0 | 750 | 0.0674 | 0.036 | 0.6249 | 0.6068 | 17.0262 |
0.0584 | 3.0 | 1125 | 0.0632 | 0.0351 | 0.6255 | 0.6075 | 16.9962 |
0.0484 | 4.0 | 1500 | 0.0605 | 0.0351 | 0.6251 | 0.6071 | 17.003 |
0.0484 | 5.0 | 1875 | 0.0596 | 0.035 | 0.6255 | 0.6075 | 17.0012 |
0.0418 | 6.0 | 2250 | 0.0602 | 0.035 | 0.6258 | 0.608 | 16.9958 |
0.0377 | 7.0 | 2625 | 0.0593 | 0.0351 | 0.6259 | 0.6079 | 17.0004 |
0.033 | 8.0 | 3000 | 0.0618 | 0.035 | 0.6257 | 0.6078 | 17.0032 |
0.033 | 9.0 | 3375 | 0.0637 | 0.035 | 0.6257 | 0.6078 | 16.998 |
0.028 | 10.0 | 3750 | 0.0645 | 0.035 | 0.6257 | 0.6079 | 16.9984 |
0.0255 | 11.0 | 4125 | 0.0650 | 0.035 | 0.6255 | 0.6078 | 17.0008 |
0.0226 | 12.0 | 4500 | 0.0748 | 0.035 | 0.6254 | 0.6076 | 16.9976 |
0.0226 | 13.0 | 4875 | 0.0714 | 0.035 | 0.6256 | 0.6079 | 16.9954 |
0.019 | 14.0 | 5250 | 0.0747 | 0.0349 | 0.6253 | 0.6077 | 16.994 |
0.0172 | 15.0 | 5625 | 0.0785 | 0.035 | 0.6257 | 0.6078 | 16.9954 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3