metadata
base_model: ai-forever/ruT5-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: my_t5_small_test
results: []
my_t5_small_test
This model is a fine-tuned version of ai-forever/ruT5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2898
- Bleu: 5.3699
- Gen Len: 16.6005
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: 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 114 | 2.7730 | 3.0092 | 15.861 |
| No log | 2.0 | 228 | 2.5655 | 3.9211 | 16.0397 |
| No log | 3.0 | 342 | 2.4573 | 4.7281 | 16.4218 |
| No log | 4.0 | 456 | 2.3735 | 5.0843 | 16.2531 |
| 3.5284 | 5.0 | 570 | 2.3490 | 5.7483 | 16.5533 |
| 3.5284 | 6.0 | 684 | 2.3254 | 5.6331 | 16.4963 |
| 3.5284 | 7.0 | 798 | 2.3095 | 5.6877 | 16.6898 |
| 3.5284 | 8.0 | 912 | 2.2949 | 5.6496 | 16.5583 |
| 2.6344 | 9.0 | 1026 | 2.2913 | 5.4792 | 16.6452 |
| 2.6344 | 10.0 | 1140 | 2.2898 | 5.3699 | 16.6005 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2