metadata
tags:
- text2text-generation
- definition-modeling
metrics:
- rouge
model-index:
- name: mt0-definition-ru-xl
results: []
language:
- ru
widget:
- text: Мы сели в тачку и поехали по ресторанам. Что такое тачка?
example_title: Definition generation
mt0-definition-ru-xl
This model is a version of mt0-xl finetuned on the Russian part of CoDWoE dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6241
- Rouge1: 0.2536
- Rouge2: 0.003
- Rougel: 0.2531
- Rougelsum: 0.2527
- Gen Len: 24.0693
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.0449 | 1.0 | 512 | 1.6755 | 0.0817 | 0.0 | 0.0778 | 0.0817 | 16.7581 |
| 1.707 | 2.0 | 1025 | 1.6182 | 0.096 | 0.0 | 0.097 | 0.1 | 15.8621 |
| 1.5398 | 3.0 | 1537 | 1.6085 | 0.1394 | 0.0034 | 0.1401 | 0.1416 | 16.4765 |
| 1.4142 | 4.0 | 2050 | 1.6016 | 0.1132 | 0.0 | 0.1132 | 0.1098 | 16.2732 |
| 1.3102 | 5.0 | 2562 | 1.6241 | 0.2082 | 0.0034 | 0.2054 | 0.2061 | 16.2877 |
| 1.2162 | 6.0 | 3075 | 1.6281 | 0.1549 | 0.0 | 0.1549 | 0.1549 | 16.1581 |
| 1.1364 | 7.0 | 3587 | 1.6622 | 0.1583 | 0.0 | 0.1575 | 0.1589 | 15.9925 |
| 1.0649 | 8.0 | 4100 | 1.6812 | 0.2033 | 0.0137 | 0.2012 | 0.2027 | 16.5099 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.13.1+rocm5.2
- Datasets 2.12.0
- Tokenizers 0.12.1