metadata
base_model: klue/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: mango-32-0.00002-10-fin
results: []
mango-32-0.00002-10-fin
This model is a fine-tuned version of klue/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.5883
- Accuracy: 0.6357
- F1: 0.6324
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: 64
- eval_batch_size: 64
- seed: 42
- 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 | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 233 | 1.7759 | 0.6095 | 0.6127 |
| No log | 2.0 | 466 | 1.8463 | 0.6030 | 0.5997 |
| 0.1567 | 3.0 | 699 | 1.8531 | 0.6297 | 0.6194 |
| 0.1567 | 4.0 | 932 | 2.0262 | 0.6183 | 0.6180 |
| 0.11 | 5.0 | 1165 | 2.1822 | 0.6167 | 0.6193 |
| 0.11 | 6.0 | 1398 | 2.3360 | 0.6380 | 0.6294 |
| 0.0622 | 7.0 | 1631 | 2.3473 | 0.6312 | 0.6286 |
| 0.0622 | 8.0 | 1864 | 2.5031 | 0.6319 | 0.6283 |
| 0.0294 | 9.0 | 2097 | 2.5552 | 0.6359 | 0.6315 |
| 0.0294 | 10.0 | 2330 | 2.5883 | 0.6357 | 0.6324 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0a0+b5021ba
- Datasets 2.6.2
- Tokenizers 0.14.1