M_gpt_v1.3
This model is a fine-tuned version of ai-forever/mGPT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4547
- Precision: 0.56
- Recall: 0.3739
- F1: 0.4484
- Accuracy: 0.9076
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4869 | 1.0 | 882 | 0.3957 | 0.5886 | 0.2987 | 0.3963 | 0.8995 |
| 0.3467 | 2.0 | 1764 | 0.3723 | 0.5572 | 0.3696 | 0.4444 | 0.9033 |
| 0.3031 | 3.0 | 2646 | 0.3709 | 0.5917 | 0.3289 | 0.4228 | 0.9082 |
| 0.2786 | 4.0 | 3528 | 0.3928 | 0.5649 | 0.3760 | 0.4515 | 0.9069 |
| 0.2629 | 5.0 | 4410 | 0.4547 | 0.56 | 0.3739 | 0.4484 | 0.9076 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3