metadata
base_model: Fsoft-AIC/videberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: results
results: []
results
This model is a fine-tuned version of Fsoft-AIC/videberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5379
- Accuracy: 0.7574
- F1: 0.8100
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4631 | 6.97 | 100 | 0.5049 | 0.7230 | 0.7699 |
| 0.3839 | 13.94 | 200 | 0.5379 | 0.7574 | 0.8100 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2