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# t5-base-mse-summarization

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8743
- Rouge1: 45.9597
- Rouge2: 26.8086
- Rougel: 39.935
- Rougelsum: 43.8897
- Bleurt: -0.7132
- Gen Len: 18.464

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Bleurt  | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|
| 1.2568        | 1.0   | 267  | 1.0472          | 41.6829 | 21.9654 | 35.4264 | 39.5556   | -0.8231 | 18.522  |
| 1.1085        | 2.0   | 534  | 0.9840          | 43.1479 | 23.3351 | 36.9244 | 40.886    | -0.7843 | 18.534  |
| 1.0548        | 3.0   | 801  | 0.9515          | 44.1511 | 24.4912 | 37.9549 | 41.9984   | -0.7702 | 18.528  |
| 1.0251        | 4.0   | 1068 | 0.9331          | 44.426  | 24.9439 | 38.2978 | 42.1731   | -0.7633 | 18.619  |
| 0.9888        | 5.0   | 1335 | 0.9201          | 45.0385 | 25.524  | 38.8681 | 42.8998   | -0.7497 | 18.523  |
| 0.9623        | 6.0   | 1602 | 0.9119          | 44.8648 | 25.469  | 38.9281 | 42.7798   | -0.7496 | 18.537  |
| 0.9502        | 7.0   | 1869 | 0.9015          | 44.9668 | 25.5041 | 38.9463 | 42.9368   | -0.7412 | 18.48   |
| 0.9316        | 8.0   | 2136 | 0.8973          | 45.3028 | 25.7232 | 39.1533 | 43.277    | -0.7318 | 18.523  |
| 0.9191        | 9.0   | 2403 | 0.8921          | 45.2901 | 25.916  | 39.2909 | 43.3022   | -0.7296 | 18.529  |
| 0.9122        | 10.0  | 2670 | 0.8889          | 45.3535 | 26.1369 | 39.4861 | 43.28     | -0.7271 | 18.545  |
| 0.8993        | 11.0  | 2937 | 0.8857          | 45.5345 | 26.1669 | 39.5656 | 43.4664   | -0.7269 | 18.474  |
| 0.8905        | 12.0  | 3204 | 0.8816          | 45.7796 | 26.4145 | 39.8117 | 43.734    | -0.7185 | 18.503  |
| 0.8821        | 13.0  | 3471 | 0.8794          | 45.7163 | 26.4314 | 39.719  | 43.6407   | -0.7211 | 18.496  |
| 0.8789        | 14.0  | 3738 | 0.8784          | 45.9097 | 26.7281 | 39.9071 | 43.8105   | -0.7127 | 18.452  |
| 0.8665        | 15.0  | 4005 | 0.8765          | 46.1148 | 26.8882 | 40.1006 | 43.988    | -0.711  | 18.443  |
| 0.8676        | 16.0  | 4272 | 0.8766          | 45.9119 | 26.7674 | 39.9001 | 43.8237   | -0.718  | 18.491  |
| 0.8637        | 17.0  | 4539 | 0.8758          | 45.9158 | 26.7153 | 39.9463 | 43.8323   | -0.7183 | 18.492  |
| 0.8622        | 18.0  | 4806 | 0.8752          | 45.9508 | 26.75   | 39.9533 | 43.8795   | -0.7144 | 18.465  |
| 0.8588        | 19.0  | 5073 | 0.8744          | 45.9192 | 26.7352 | 39.8921 | 43.8204   | -0.7148 | 18.462  |
| 0.8554        | 20.0  | 5340 | 0.8743          | 45.9597 | 26.8086 | 39.935  | 43.8897   | -0.7132 | 18.464  |


### Framework versions

- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

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

t5-base-mse-summarization
=========================


This model is a fine-tuned version of t5-base on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.8743
* Rouge1: 45.9597
* Rouge2: 26.8086
* Rougel: 39.935
* Rougelsum: 43.8897
* Bleurt: -0.7132
* Gen Len: 18.464


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: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20


### Training results



### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #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: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20 ### Training results ### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #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: 1e-05
* train\_batch\_size: 16
* eval\_batch\_size: 16
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20### Training results### Framework versions


* Transformers 4.21.2
* Pytorch 1.12.1+cu113
* Datasets 2.4.0
* Tokenizers 0.12.1