---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-large-gramatika161k-b16-e10-lr0.001
  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-lr0.001

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: 0.1537
- Rouge1: 70.8264
- Rouge2: 64.518
- Rougel: 70.6934
- Rougelsum: 70.6881
- Gen Len: 18.3298

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.3641        | 0.63  | 5000  | 0.1944          | 69.4204 | 61.9635 | 69.2556 | 69.2477   | 18.3389 |
| 0.1843        | 1.27  | 10000 | 0.1655          | 70.3343 | 63.6924 | 70.1851 | 70.1815   | 18.3377 |
| 0.1359        | 1.9   | 15000 | 0.1537          | 70.8264 | 64.518  | 70.6934 | 70.6881   | 18.3298 |
| 0.0912        | 2.54  | 20000 | 0.1643          | 71.037  | 64.8861 | 70.9075 | 70.9027   | 18.3295 |
| 0.0759        | 3.17  | 25000 | 0.1694          | 71.288  | 65.3505 | 71.1746 | 71.1675   | 18.3314 |
| 0.054         | 3.81  | 30000 | 0.1672          | 71.4356 | 65.5825 | 71.3263 | 71.3199   | 18.3294 |
| 0.0398        | 4.44  | 35000 | 0.1779          | 71.4473 | 65.6798 | 71.343  | 71.3354   | 18.3341 |
| 0.0331        | 5.08  | 40000 | 0.1908          | 71.615  | 65.9285 | 71.5126 | 71.4982   | 18.3344 |
| 0.021         | 5.71  | 45000 | 0.2025          | 71.6252 | 65.9628 | 71.5172 | 71.513    | 18.3317 |
| 0.0167        | 6.35  | 50000 | 0.2107          | 71.6508 | 66.0666 | 71.5547 | 71.542    | 18.3366 |
| 0.0126        | 6.98  | 55000 | 0.2084          | 71.8403 | 66.3396 | 71.7392 | 71.735    | 18.3337 |
| 0.0072        | 7.62  | 60000 | 0.2256          | 71.8659 | 66.388  | 71.7699 | 71.7644   | 18.3330 |
| 0.0057        | 8.25  | 65000 | 0.2578          | 71.9226 | 66.4948 | 71.8279 | 71.8162   | 18.3313 |
| 0.0036        | 8.88  | 70000 | 0.2784          | 71.9279 | 66.5248 | 71.8258 | 71.8149   | 18.3324 |
| 0.0021        | 9.52  | 75000 | 0.3040          | 71.9913 | 66.634  | 71.893  | 71.8844   | 18.3317 |


### Framework versions

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