transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:squad license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- squad
license: apache-2.0
metrics:
- rouge
- bleu
tags:
- generated_from_trainer
model-index:
- name: flan-t5-qg-tarek-test-SQUAD
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: squad
      type: squad
      config: plain_text
      split: validation
      args: plain_text
    metrics:
    - type: rouge
      value: 51.7909
      name: Rouge1
    - type: bleu
      value:
        bleu: 0.20591622940642762
        precisions:
        - 0.5204716701541998
        - 0.2619394913622878
        - 0.1654269529647818
        - 0.10906716558470096
        brevity_penalty: 0.9246257500068106
        length_ratio: 0.927328752862794
        translation_length: 111349
        reference_length: 120075
      name: Bleu
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# flan-t5-qg-tarek-test-SQUAD

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6101
- Rouge1: 51.7909
- Rouge2: 29.105
- Rougel: 47.9342
- Rougelsum: 47.9206
- Gen Len: 14.3335
- Meteor: {'meteor': 0.46880070390780776}
- Bleu: {'bleu': 0.20591622940642762, 'precisions': [0.5204716701541998, 0.2619394913622878, 0.1654269529647818, 0.10906716558470096], 'brevity_penalty': 0.9246257500068106, 'length_ratio': 0.927328752862794, 'translation_length': 111349, 'reference_length': 120075}

## 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: 0.0005
- 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: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len | Meteor                          | Bleu                                                                                                                                                                                                                                                                 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| 0.6576        | 1.0   | 10950 | 0.6301          | 50.2515 | 27.5194 | 46.5001 | 46.4993   | 14.0607 | {'meteor': 0.44978235923873977} | {'bleu': 0.19104342466719015, 'precisions': [0.5159747201089206, 0.2503337307531615, 0.15519111953679066, 0.10098320626550465], 'brevity_penalty': 0.9006709188377698, 'length_ratio': 0.9052925255048928, 'translation_length': 108703, 'reference_length': 120075} |
| 0.5315        | 2.0   | 21900 | 0.6101          | 51.7909 | 29.105  | 47.9342 | 47.9206   | 14.3335 | {'meteor': 0.46880070390780776} | {'bleu': 0.20591622940642762, 'precisions': [0.5204716701541998, 0.2619394913622878, 0.1654269529647818, 0.10906716558470096], 'brevity_penalty': 0.9246257500068106, 'length_ratio': 0.927328752862794, 'translation_length': 111349, 'reference_length': 120075}   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
