File size: 2,574 Bytes
b6765e8 |
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 |
---
license: mit
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: fine-tuned-DatasetQAS-IDK-MRC-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05
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. -->
# fine-tuned-DatasetQAS-IDK-MRC-with-indobert-large-p2-with-ITTL-without-freeze-LR-1e-05
This model is a fine-tuned version of [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2364
- Exact Match: 50.2618
- F1: 57.5214
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:-------:|
| 6.151 | 0.49 | 36 | 2.7223 | 32.5916 | 35.4445 |
| 3.5424 | 0.98 | 72 | 2.0664 | 24.2147 | 31.0371 |
| 2.2082 | 1.48 | 108 | 1.7388 | 28.0105 | 37.2690 |
| 2.2082 | 1.97 | 144 | 1.4742 | 37.0419 | 45.3625 |
| 1.6932 | 2.46 | 180 | 1.3193 | 43.3246 | 51.1270 |
| 1.3154 | 2.95 | 216 | 1.2731 | 46.2042 | 53.5503 |
| 1.1699 | 3.45 | 252 | 1.2327 | 46.4660 | 53.5656 |
| 1.1699 | 3.94 | 288 | 1.1998 | 48.1675 | 55.1907 |
| 1.0749 | 4.44 | 324 | 1.1949 | 51.0471 | 57.7164 |
| 0.9423 | 4.93 | 360 | 1.1855 | 50.6545 | 57.3903 |
| 0.9423 | 5.42 | 396 | 1.1931 | 51.3089 | 58.5981 |
| 0.9036 | 5.91 | 432 | 1.2045 | 50.3927 | 57.7468 |
| 0.8324 | 6.41 | 468 | 1.2363 | 48.2984 | 55.5302 |
| 0.7846 | 6.9 | 504 | 1.2364 | 50.2618 | 57.5214 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2
|