File size: 2,811 Bytes
f6c5562 |
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-python
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-python
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: 0.7802
- Bleu: 0.0027
- Rouge1: 0.2097
- Rouge2: 0.0628
- Avg Length: 15.7496
## 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 | 0.9665 | 0.0004 | 0.1696 | 0.0384 | 14.1472 |
| 2.0677 | 2.0 | 750 | 0.8740 | 0.0004 | 0.1758 | 0.0428 | 13.38 |
| 0.8314 | 3.0 | 1125 | 0.8281 | 0.001 | 0.1925 | 0.0505 | 14.8026 |
| 0.7563 | 4.0 | 1500 | 0.7996 | 0.0017 | 0.2033 | 0.0582 | 14.9606 |
| 0.7563 | 5.0 | 1875 | 0.7780 | 0.0022 | 0.2117 | 0.0607 | 14.9434 |
| 0.6959 | 6.0 | 2250 | 0.7587 | 0.002 | 0.2135 | 0.0621 | 14.6926 |
| 0.6591 | 7.0 | 2625 | 0.7545 | 0.002 | 0.2073 | 0.0605 | 15.2818 |
| 0.6205 | 8.0 | 3000 | 0.7472 | 0.0024 | 0.2187 | 0.0674 | 15.051 |
| 0.6205 | 9.0 | 3375 | 0.7506 | 0.0031 | 0.2266 | 0.0696 | 15.6286 |
| 0.5822 | 10.0 | 3750 | 0.7449 | 0.001 | 0.206 | 0.063 | 13.1462 |
| 0.5553 | 11.0 | 4125 | 0.7573 | 0.0027 | 0.2148 | 0.0647 | 16.4076 |
| 0.5295 | 12.0 | 4500 | 0.7677 | 0.0026 | 0.2185 | 0.0658 | 15.8986 |
| 0.5295 | 13.0 | 4875 | 0.7595 | 0.0009 | 0.2052 | 0.0618 | 12.3528 |
| 0.4977 | 14.0 | 5250 | 0.7766 | 0.0035 | 0.2177 | 0.0636 | 16.6706 |
| 0.4818 | 15.0 | 5625 | 0.7802 | 0.0027 | 0.2097 | 0.0628 | 15.7496 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|