---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-large-gramatika161k-b16-e10-lr5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# mt5-large-gramatika161k-b16-e10-lr5

This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0909
- Rouge1: 72.6295
- Rouge2: 67.8521
- Rougel: 72.5471
- Rougelsum: 72.5591
- Gen Len: 18.3276

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.9659        | 0.63  | 5000  | 0.1455          | 70.1028 | 63.4969 | 69.9738 | 69.9761   | 18.3378 |
| 0.1735        | 1.27  | 10000 | 0.1195          | 71.1156 | 65.2149 | 70.9932 | 71.0038   | 18.3324 |
| 0.1391        | 1.9   | 15000 | 0.1076          | 71.5692 | 66.0226 | 71.4676 | 71.472    | 18.3281 |
| 0.1149        | 2.54  | 20000 | 0.1035          | 71.8135 | 66.4584 | 71.7212 | 71.7292   | 18.3308 |
| 0.1029        | 3.17  | 25000 | 0.0961          | 72.104  | 66.9459 | 72.0139 | 72.0239   | 18.3282 |
| 0.0898        | 3.81  | 30000 | 0.0944          | 72.231  | 67.1623 | 72.1412 | 72.1542   | 18.3314 |
| 0.0803        | 4.44  | 35000 | 0.0926          | 72.3851 | 67.4624 | 72.3051 | 72.3183   | 18.3286 |
| 0.075         | 5.08  | 40000 | 0.0929          | 72.4219 | 67.5102 | 72.3376 | 72.3479   | 18.3298 |
| 0.0665        | 5.71  | 45000 | 0.0917          | 72.5132 | 67.6501 | 72.4271 | 72.4383   | 18.3264 |
| 0.0624        | 6.35  | 50000 | 0.0911          | 72.5711 | 67.771  | 72.4938 | 72.5041   | 18.3283 |
| 0.0588        | 6.98  | 55000 | 0.0909          | 72.6295 | 67.8521 | 72.5471 | 72.5591   | 18.3276 |
| 0.0534        | 7.62  | 60000 | 0.0920          | 72.6475 | 67.9046 | 72.5743 | 72.5853   | 18.3278 |
| 0.0514        | 8.25  | 65000 | 0.0930          | 72.6373 | 67.894  | 72.5612 | 72.5724   | 18.3277 |
| 0.0492        | 8.88  | 70000 | 0.0930          | 72.6593 | 67.9359 | 72.59   | 72.5971   | 18.3273 |
| 0.047         | 9.52  | 75000 | 0.0932          | 72.6906 | 68.01   | 72.6172 | 72.6269   | 18.3264 |


### Framework versions

- Transformers 4.30.1
- Pytorch 1.11.0a0+b6df043
- Datasets 2.12.0
- Tokenizers 0.13.3