transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-base license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: oop-de-qg-flan-t5-base-v3
  results: []
---

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# oop-de-qg-flan-t5-base-v3

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 8.0858
- Rouge2: 3.0935
- Rougel: 7.2494
- Rougelsum: 7.3009
- Gen Len: 58.0151
- Bleu: 0.0107
- Precisions: [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211]
- Brevity Penalty: 1.0
- Length Ratio: 4.2235
- Translation Length: 15323
- Reference Length: 3628

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bleu   | Precisions                                                                              | Brevity Penalty | Length Ratio | Translation Length | Reference Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:---------------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|
| No log        | 1.0   | 291  | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 2.0   | 582  | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 3.0   | 873  | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 4.0   | 1164 | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 5.0   | 1455 | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 6.0   | 1746 | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 7.0   | 2037 | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 8.0   | 2328 | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 9.0   | 2619 | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |
| 0.0           | 10.0  | 2910 | nan             | 8.0858 | 3.0935 | 7.2494 | 7.3009    | 58.0151 | 0.0107 | [0.04098414148665405, 0.014941302027748132, 0.007025441647909419, 0.003000697836706211] | 1.0             | 4.2235       | 15323              | 3628             |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
