metadata
base_model: monologg/distilkobert
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: distilkobert-KEmoFact-EFE-0927
results: []
distilkobert-KEmoFact-EFE-0927
This model is a fine-tuned version of monologg/distilkobert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6353
- Precision: 0.1922
- Recall: 0.1524
- F1: 0.17
- Ov Accuracy: 0.7154
- Jaccard: 0.4371
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Ov Accuracy | Jaccard |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 414 | 0.6729 | 0.1195 | 0.0967 | 0.1069 | 0.6943 | 0.3858 |
| 0.7003 | 2.0 | 828 | 0.6687 | 0.1438 | 0.1261 | 0.1344 | 0.6932 | 0.4298 |
| 0.6537 | 3.0 | 1242 | 0.6563 | 0.1463 | 0.1052 | 0.1224 | 0.7017 | 0.3558 |
| 0.64 | 4.0 | 1656 | 0.6613 | 0.1484 | 0.1160 | 0.1302 | 0.7019 | 0.3975 |
| 0.6323 | 5.0 | 2070 | 0.6563 | 0.1467 | 0.1160 | 0.1295 | 0.7028 | 0.3960 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3