File size: 5,229 Bytes
55360d7 83b7ffa 55360d7 83b7ffa 55360d7 83b7ffa 55360d7 83b7ffa 55360d7 |
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 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 |
---
license: apache-2.0
tags:
- distigpt2
- hearthstone
metrics:
- bleu
- dvitel/codebleu
- exact_match
- chrf
datasets:
- dvitel/hearthstone
model-index:
- name: h0
results:
- task:
type: text-generation
name: Python Code Synthesis
dataset:
type: dvitel/hearthstone
name: HearthStone
split: test
metrics:
- type: exact_match
value: 0.0
name: Exact Match
- type: bleu
value: 0.6082316056517667
name: BLEU
- type: dvitel/codebleu
value: 0.36984242128954287
name: CodeBLEU
- type: chrf
value: 68.77878158023694
name: chrF
---
# h2
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on [hearthstone](https://huggingface.co/datasets/dvitel/hearthstone).
[GitHub repo](https://github.com/dvitel/nlp-sem-parsing/blob/master/h2.py).
It achieves the following results on the evaluation set:
- Loss: 2.5771
- Exact Match: 0.0
- Bleu: 0.6619
- Codebleu: 0.5374
- Ngram Match Score: 0.4051
- Weighted Ngram Match Score: 0.4298
- Syntax Match Score: 0.5605
- Dataflow Match Score: 0.7541
- Chrf: 73.9625
## 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: 4
- eval_batch_size: 4
- seed: 17
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | Bleu | Codebleu | Ngram Match Score | Weighted Ngram Match Score | Syntax Match Score | Dataflow Match Score | Chrf |
|:-------------:|:------:|:-----:|:---------------:|:-----------:|:------:|:--------:|:-----------------:|:--------------------------:|:------------------:|:--------------------:|:-------:|
| 1.2052 | 11.94 | 1600 | 1.2887 | 0.0 | 0.6340 | 0.4427 | 0.3384 | 0.3614 | 0.5263 | 0.5446 | 70.8004 |
| 0.3227 | 23.88 | 3200 | 1.4484 | 0.0 | 0.6575 | 0.5050 | 0.3767 | 0.3995 | 0.5955 | 0.6485 | 72.9553 |
| 0.205 | 35.82 | 4800 | 1.6392 | 0.0 | 0.6598 | 0.5174 | 0.3788 | 0.4022 | 0.5821 | 0.7063 | 73.2766 |
| 0.1392 | 47.76 | 6400 | 1.8219 | 0.0 | 0.6584 | 0.5279 | 0.3922 | 0.4159 | 0.5742 | 0.7294 | 73.5022 |
| 0.0979 | 59.7 | 8000 | 1.9416 | 0.0 | 0.6635 | 0.5305 | 0.4012 | 0.4248 | 0.5699 | 0.7261 | 73.8081 |
| 0.0694 | 71.64 | 9600 | 2.1793 | 0.0 | 0.6593 | 0.5400 | 0.4027 | 0.4271 | 0.5562 | 0.7739 | 73.6746 |
| 0.0512 | 83.58 | 11200 | 2.2547 | 0.0 | 0.6585 | 0.5433 | 0.4040 | 0.4283 | 0.5486 | 0.7921 | 73.7670 |
| 0.0399 | 95.52 | 12800 | 2.3037 | 0.0 | 0.6585 | 0.5354 | 0.4040 | 0.4282 | 0.5454 | 0.7640 | 73.7431 |
| 0.0316 | 107.46 | 14400 | 2.4113 | 0.0 | 0.6577 | 0.5294 | 0.4006 | 0.4257 | 0.5504 | 0.7409 | 73.7004 |
| 0.0254 | 119.4 | 16000 | 2.4407 | 0.0 | 0.6607 | 0.5412 | 0.4041 | 0.4285 | 0.5598 | 0.7723 | 73.8828 |
| 0.0208 | 131.34 | 17600 | 2.4993 | 0.0 | 0.6637 | 0.5330 | 0.4042 | 0.4286 | 0.5684 | 0.7310 | 74.1760 |
| 0.0176 | 143.28 | 19200 | 2.5138 | 0.0 | 0.6627 | 0.5434 | 0.4050 | 0.4295 | 0.5620 | 0.7772 | 74.0546 |
| 0.0158 | 155.22 | 20800 | 2.5589 | 0.0 | 0.6616 | 0.5347 | 0.4044 | 0.4291 | 0.5512 | 0.7541 | 73.9516 |
| 0.0147 | 167.16 | 22400 | 2.5554 | 0.0 | 0.6620 | 0.5354 | 0.4049 | 0.4295 | 0.5630 | 0.7442 | 73.9461 |
| 0.0134 | 179.1 | 24000 | 2.5696 | 0.0 | 0.6607 | 0.5395 | 0.4046 | 0.4293 | 0.5602 | 0.7640 | 73.8383 |
| 0.0135 | 191.04 | 25600 | 2.5771 | 0.0 | 0.6619 | 0.5374 | 0.4051 | 0.4298 | 0.5605 | 0.7541 | 73.9625 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1
|