---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: skilltext
  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. -->

# skilltext

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.431
- Rouge2: 0.0
- Rougel: 0.431
- Rougelsum: 0.431
- Bleu: 0.0322
- Gen Len: 11.75

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu   | Gen Len |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:-------:|
| No log        | 0.8065  | 50   | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 1.6129  | 100  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 2.4194  | 150  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 3.2258  | 200  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 4.0323  | 250  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 4.8387  | 300  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 5.6452  | 350  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 6.4516  | 400  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| No log        | 7.2581  | 450  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 8.0645  | 500  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 8.8710  | 550  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 9.6774  | 600  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 10.4839 | 650  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 11.2903 | 700  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 12.0968 | 750  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 12.9032 | 800  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 13.7097 | 850  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 14.5161 | 900  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 15.3226 | 950  | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 16.1290 | 1000 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 16.9355 | 1050 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 17.7419 | 1100 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 18.5484 | 1150 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 19.3548 | 1200 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 20.1613 | 1250 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 20.9677 | 1300 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 21.7742 | 1350 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 22.5806 | 1400 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 23.3871 | 1450 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 24.1935 | 1500 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 25.0    | 1550 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 25.8065 | 1600 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 26.6129 | 1650 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 27.4194 | 1700 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 28.2258 | 1750 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 29.0323 | 1800 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |
| 0.0           | 29.8387 | 1850 | nan             | 0.431  | 0.0    | 0.431  | 0.431     | 0.0322 | 11.75   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2
- Datasets 2.12.0
- Tokenizers 0.19.1