
# mt0-definition-ru-xl

This model is a version of [mt0-xl](https://huggingface.co/bigscience/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

{"language": ["ru"], "tags": ["text2text-generation", "definition-modeling"], "metrics": ["rouge"], "widget": [{"text": "\u041c\u044b \u0441\u0435\u043b\u0438 \u0432 \u0442\u0430\u0447\u043a\u0443 \u0438 \u043f\u043e\u0435\u0445\u0430\u043b\u0438 \u043f\u043e \u0440\u0435\u0441\u0442\u043e\u0440\u0430\u043d\u0430\u043c. \u0427\u0442\u043e \u0442\u0430\u043a\u043e\u0435 \u0442\u0430\u0447\u043a\u0430?", "example_title": "Definition generation"}], "model-index": [{"name": "mt0-definition-ru-xl", "results": []}]}
transformers pytorch mt5 text2text-generation definition-modeling ru autotrain_compatible endpoints_compatible text-generation-inference region:us