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# flan-t5-base-TriviaQA-qag-ep10

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3620
- Rouge1: 39.8143
- Rouge2: 17.6525
- Rougel: 33.7284
- Rougelsum: 33.7443
- F1: 11.1984
- Exact Match: 8.4778
- Gen Len: 18.7224

## 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: 72
- eval_batch_size: 144
- seed: 1799
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | F1      | Exact Match | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-----------:|:-------:|
| 1.718         | 0.58  | 500  | 1.4892          | 36.7354 | 14.5408 | 30.6756 | 30.6799   | 8.9323  | 6.2428      | 18.7535 |
| 1.6019        | 1.17  | 1000 | 1.4516          | 37.5084 | 15.1746 | 31.3612 | 31.3617   | 9.3629  | 6.885       | 18.7486 |
| 1.5581        | 1.75  | 1500 | 1.4303          | 37.8554 | 15.5686 | 31.7633 | 31.7591   | 10.2193 | 7.6044      | 18.7371 |
| 1.5273        | 2.33  | 2000 | 1.4158          | 38.1533 | 15.9332 | 32.103  | 32.1008   | 10.1181 | 7.5273      | 18.7349 |
| 1.5096        | 2.92  | 2500 | 1.4040          | 38.5218 | 16.3547 | 32.4545 | 32.4433   | 10.6931 | 8.0283      | 18.7178 |
| 1.4864        | 3.5   | 3000 | 1.3956          | 39.0574 | 16.8492 | 33.019  | 33.0265   | 10.8949 | 8.2209      | 18.7097 |
| 1.4785        | 4.08  | 3500 | 1.3890          | 38.9339 | 16.7759 | 32.8597 | 32.8672   | 10.5823 | 7.9769      | 18.7178 |
| 1.4622        | 4.67  | 4000 | 1.3826          | 39.2009 | 16.9529 | 33.1057 | 33.1127   | 10.9865 | 8.3751      | 18.7155 |
| 1.4505        | 5.25  | 4500 | 1.3779          | 39.3368 | 17.2173 | 33.2987 | 33.3018   | 10.9311 | 8.3109      | 18.7138 |
| 1.4483        | 5.83  | 5000 | 1.3728          | 39.7136 | 17.5316 | 33.607  | 33.6267   | 10.575  | 7.9512      | 18.7297 |
| 1.4329        | 6.42  | 5500 | 1.3706          | 39.4669 | 17.3885 | 33.412  | 33.4095   | 10.8311 | 8.2595      | 18.7306 |
| 1.4311        | 7.0   | 6000 | 1.3677          | 39.6353 | 17.4778 | 33.5505 | 33.5499   | 11.0071 | 8.4136      | 18.724  |
| 1.4229        | 7.58  | 6500 | 1.3661          | 39.6099 | 17.511  | 33.5553 | 33.5608   | 11.0084 | 8.4008      | 18.7231 |
| 1.4213        | 8.17  | 7000 | 1.3638          | 39.7805 | 17.6628 | 33.6967 | 33.7052   | 10.9316 | 8.3622      | 18.7141 |
| 1.4112        | 8.75  | 7500 | 1.3625          | 39.7281 | 17.6079 | 33.6809 | 33.6946   | 11.1526 | 8.4522      | 18.718  |
| 1.4141        | 9.33  | 8000 | 1.3623          | 39.6856 | 17.5403 | 33.5985 | 33.6198   | 11.1693 | 8.465       | 18.7188 |
| 1.4139        | 9.92  | 8500 | 1.3620          | 39.8143 | 17.6525 | 33.7284 | 33.7443   | 11.1984 | 8.4778      | 18.7224 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge", "f1"], "model-index": [{"name": "flan-t5-base-TriviaQA-qag-ep10", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

flan-t5-base-TriviaQA-qag-ep10
==============================


This model is a fine-tuned version of google/flan-t5-base on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.3620
* Rouge1: 39.8143
* Rouge2: 17.6525
* Rougel: 33.7284
* Rougelsum: 33.7443
* F1: 11.1984
* Exact Match: 8.4778
* Gen Len: 18.7224


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: 72
* eval\_batch\_size: 144
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.5.1
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 72
* eval\_batch\_size: 144
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.5.1
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 72
* eval\_batch\_size: 144
* seed: 1799
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.11.0+cu113
* Datasets 2.5.1
* Tokenizers 0.12.1