End of training
Browse files
README.md
ADDED
|
@@ -0,0 +1,70 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: klue/roberta-large
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
- f1
|
| 8 |
+
model-index:
|
| 9 |
+
- name: mango-32-0.00002-10-fin
|
| 10 |
+
results: []
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 14 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 15 |
+
|
| 16 |
+
# mango-32-0.00002-10-fin
|
| 17 |
+
|
| 18 |
+
This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on the None dataset.
|
| 19 |
+
It achieves the following results on the evaluation set:
|
| 20 |
+
- Loss: 2.5883
|
| 21 |
+
- Accuracy: 0.6357
|
| 22 |
+
- F1: 0.6324
|
| 23 |
+
|
| 24 |
+
## Model description
|
| 25 |
+
|
| 26 |
+
More information needed
|
| 27 |
+
|
| 28 |
+
## Intended uses & limitations
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Training and evaluation data
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training procedure
|
| 37 |
+
|
| 38 |
+
### Training hyperparameters
|
| 39 |
+
|
| 40 |
+
The following hyperparameters were used during training:
|
| 41 |
+
- learning_rate: 2e-05
|
| 42 |
+
- train_batch_size: 64
|
| 43 |
+
- eval_batch_size: 64
|
| 44 |
+
- seed: 42
|
| 45 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 46 |
+
- lr_scheduler_type: linear
|
| 47 |
+
- num_epochs: 10
|
| 48 |
+
|
| 49 |
+
### Training results
|
| 50 |
+
|
| 51 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|
| 52 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
|
| 53 |
+
| No log | 1.0 | 233 | 1.7759 | 0.6095 | 0.6127 |
|
| 54 |
+
| No log | 2.0 | 466 | 1.8463 | 0.6030 | 0.5997 |
|
| 55 |
+
| 0.1567 | 3.0 | 699 | 1.8531 | 0.6297 | 0.6194 |
|
| 56 |
+
| 0.1567 | 4.0 | 932 | 2.0262 | 0.6183 | 0.6180 |
|
| 57 |
+
| 0.11 | 5.0 | 1165 | 2.1822 | 0.6167 | 0.6193 |
|
| 58 |
+
| 0.11 | 6.0 | 1398 | 2.3360 | 0.6380 | 0.6294 |
|
| 59 |
+
| 0.0622 | 7.0 | 1631 | 2.3473 | 0.6312 | 0.6286 |
|
| 60 |
+
| 0.0622 | 8.0 | 1864 | 2.5031 | 0.6319 | 0.6283 |
|
| 61 |
+
| 0.0294 | 9.0 | 2097 | 2.5552 | 0.6359 | 0.6315 |
|
| 62 |
+
| 0.0294 | 10.0 | 2330 | 2.5883 | 0.6357 | 0.6324 |
|
| 63 |
+
|
| 64 |
+
|
| 65 |
+
### Framework versions
|
| 66 |
+
|
| 67 |
+
- Transformers 4.34.1
|
| 68 |
+
- Pytorch 2.1.0a0+b5021ba
|
| 69 |
+
- Datasets 2.6.2
|
| 70 |
+
- Tokenizers 0.14.1
|