metadata
license: cc-by-sa-4.0
library_name: peft
tags:
- generated_from_trainer
base_model: EMBEDDIA/sloberta
metrics:
- accuracy
- f1
model-index:
- name: prompt_fine_tuned_CB_sloberta
results: []
prompt_fine_tuned_CB_sloberta
This model is a fine-tuned version of EMBEDDIA/sloberta on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3650
- Accuracy: 0.3182
- F1: 0.1536
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: 0.003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
1.5028 | 0.4545 | 50 | 5.1956 | 0.3182 | 0.1591 |
2.1341 | 0.9091 | 100 | 4.9336 | 0.3182 | 0.1536 |
1.2666 | 1.3636 | 150 | 5.4769 | 0.3182 | 0.1536 |
1.7486 | 1.8182 | 200 | 4.4089 | 0.3182 | 0.1536 |
1.5321 | 2.2727 | 250 | 3.3006 | 0.4545 | 0.3895 |
1.296 | 2.7273 | 300 | 3.3196 | 0.3182 | 0.1536 |
1.3419 | 3.1818 | 350 | 3.1575 | 0.3182 | 0.1536 |
1.0893 | 3.6364 | 400 | 3.3650 | 0.3182 | 0.1536 |
Framework versions
- PEFT 0.11.1
- Transformers 4.40.2
- Pytorch 2.1.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1