File size: 2,664 Bytes
b816dfd 9920a15 b816dfd |
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 |
---
base_model: aubmindlab/aragpt2-base
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: res_nw_yem_aragpt2-base
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. -->
# res_nw_yem_aragpt2-base
This model is a fine-tuned version of [aubmindlab/aragpt2-base](https://huggingface.co/aubmindlab/aragpt2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0534
- Bleu: 0.0428
- Rouge1: 0.3139
- Rouge2: 0.1104
- Rougel: 0.3097
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|
| 5.8224 | 1.0 | 153 | 0.1129 | 0.0039 | 0.0712 | 0.0029 | 0.0695 |
| 0.1108 | 2.0 | 306 | 0.0691 | 0.0 | 0.0951 | 0.0078 | 0.0932 |
| 0.0775 | 3.0 | 459 | 0.0628 | 0.0067 | 0.1291 | 0.0157 | 0.1286 |
| 0.0678 | 4.0 | 612 | 0.0592 | 0.0086 | 0.1524 | 0.0273 | 0.1492 |
| 0.0603 | 5.0 | 765 | 0.0566 | 0.0162 | 0.1919 | 0.0413 | 0.1883 |
| 0.0547 | 6.0 | 918 | 0.0546 | 0.0187 | 0.2239 | 0.0599 | 0.2218 |
| 0.0498 | 7.0 | 1071 | 0.0540 | 0.0295 | 0.2684 | 0.0733 | 0.2638 |
| 0.0456 | 8.0 | 1224 | 0.0536 | 0.0292 | 0.2884 | 0.0818 | 0.2841 |
| 0.0419 | 9.0 | 1377 | 0.0534 | 0.0428 | 0.3139 | 0.1104 | 0.3097 |
| 0.0385 | 10.0 | 1530 | 0.0534 | 0.0461 | 0.3255 | 0.1118 | 0.3185 |
| 0.0354 | 11.0 | 1683 | 0.0540 | 0.0473 | 0.3358 | 0.1219 | 0.3288 |
| 0.0331 | 12.0 | 1836 | 0.0540 | 0.0476 | 0.3483 | 0.1312 | 0.3442 |
| 0.0308 | 13.0 | 1989 | 0.0552 | 0.0590 | 0.3599 | 0.1439 | 0.3539 |
| 0.0291 | 14.0 | 2142 | 0.0556 | 0.0625 | 0.3737 | 0.1489 | 0.3670 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|