metadata
library_name: transformers
license: mit
base_model: seara/rubert-tiny2-russian-sentiment
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: rubert-tiny2-sentiment-tuned
results: []
rubert-tiny2-sentiment-tuned
This model is a fine-tuned version of seara/rubert-tiny2-russian-sentiment on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2380
- Accuracy: 0.9248
- F1: 0.9274
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: 3e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4865 | 0.1926 | 500 | 0.3455 | 0.8853 | 0.9123 |
| 0.3198 | 0.3852 | 1000 | 0.2753 | 0.9127 | 0.9218 |
| 0.2655 | 0.5778 | 1500 | 0.2513 | 0.9217 | 0.9260 |
| 0.2506 | 0.7704 | 2000 | 0.2415 | 0.9240 | 0.9270 |
| 0.2511 | 0.9630 | 2500 | 0.2380 | 0.9248 | 0.9274 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0