Model save
Browse files- README.md +77 -0
- model.safetensors +1 -1
README.md
ADDED
|
@@ -0,0 +1,77 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
base_model: indobenchmark/indobert-base-p1
|
| 4 |
+
tags:
|
| 5 |
+
- generated_from_trainer
|
| 6 |
+
metrics:
|
| 7 |
+
- accuracy
|
| 8 |
+
- f1
|
| 9 |
+
- precision
|
| 10 |
+
- recall
|
| 11 |
+
model-index:
|
| 12 |
+
- name: indobert-base-p1-twitter-indonesia-sarcastic
|
| 13 |
+
results: []
|
| 14 |
+
---
|
| 15 |
+
|
| 16 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 17 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 18 |
+
|
| 19 |
+
# indobert-base-p1-twitter-indonesia-sarcastic
|
| 20 |
+
|
| 21 |
+
This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co/indobenchmark/indobert-base-p1) on an unknown dataset.
|
| 22 |
+
It achieves the following results on the evaluation set:
|
| 23 |
+
- Loss: 1.0108
|
| 24 |
+
- Accuracy: 0.8619
|
| 25 |
+
- F1: 0.7176
|
| 26 |
+
- Precision: 0.7344
|
| 27 |
+
- Recall: 0.7015
|
| 28 |
+
|
| 29 |
+
## Model description
|
| 30 |
+
|
| 31 |
+
More information needed
|
| 32 |
+
|
| 33 |
+
## Intended uses & limitations
|
| 34 |
+
|
| 35 |
+
More information needed
|
| 36 |
+
|
| 37 |
+
## Training and evaluation data
|
| 38 |
+
|
| 39 |
+
More information needed
|
| 40 |
+
|
| 41 |
+
## Training procedure
|
| 42 |
+
|
| 43 |
+
### Training hyperparameters
|
| 44 |
+
|
| 45 |
+
The following hyperparameters were used during training:
|
| 46 |
+
- learning_rate: 1e-05
|
| 47 |
+
- train_batch_size: 32
|
| 48 |
+
- eval_batch_size: 64
|
| 49 |
+
- seed: 42
|
| 50 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 51 |
+
- lr_scheduler_type: cosine
|
| 52 |
+
- num_epochs: 100.0
|
| 53 |
+
- mixed_precision_training: Native AMP
|
| 54 |
+
|
| 55 |
+
### Training results
|
| 56 |
+
|
| 57 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|
| 58 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
|
| 59 |
+
| 0.5101 | 1.0 | 59 | 0.4221 | 0.7836 | 0.6081 | 0.5556 | 0.6716 |
|
| 60 |
+
| 0.3508 | 2.0 | 118 | 0.3479 | 0.8246 | 0.6713 | 0.6316 | 0.7164 |
|
| 61 |
+
| 0.221 | 3.0 | 177 | 0.3511 | 0.8582 | 0.6935 | 0.7544 | 0.6418 |
|
| 62 |
+
| 0.1157 | 4.0 | 236 | 0.4352 | 0.8396 | 0.6861 | 0.6714 | 0.7015 |
|
| 63 |
+
| 0.0453 | 5.0 | 295 | 0.6923 | 0.8582 | 0.7077 | 0.7302 | 0.6866 |
|
| 64 |
+
| 0.0192 | 6.0 | 354 | 0.7378 | 0.8694 | 0.7287 | 0.7581 | 0.7015 |
|
| 65 |
+
| 0.0159 | 7.0 | 413 | 0.8860 | 0.8545 | 0.6723 | 0.7692 | 0.5970 |
|
| 66 |
+
| 0.0165 | 8.0 | 472 | 0.8261 | 0.8694 | 0.7445 | 0.7286 | 0.7612 |
|
| 67 |
+
| 0.0175 | 9.0 | 531 | 0.8732 | 0.8731 | 0.7424 | 0.7538 | 0.7313 |
|
| 68 |
+
| 0.0062 | 10.0 | 590 | 0.9648 | 0.8657 | 0.7273 | 0.7385 | 0.7164 |
|
| 69 |
+
| 0.0003 | 11.0 | 649 | 1.0108 | 0.8619 | 0.7176 | 0.7344 | 0.7015 |
|
| 70 |
+
|
| 71 |
+
|
| 72 |
+
### Framework versions
|
| 73 |
+
|
| 74 |
+
- Transformers 4.36.2
|
| 75 |
+
- Pytorch 2.1.1+cu121
|
| 76 |
+
- Datasets 2.15.0
|
| 77 |
+
- Tokenizers 0.15.0
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 497795072
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7a47cdc299eb06c8191068041dcd67f8427d801ef8e351e66d4be3c636394ae0
|
| 3 |
size 497795072
|