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# t5-base-snl

This model is a fine-tuned version of [north/t5_base_NCC_lm](https://huggingface.co/north/t5_base_NCC_lm) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0574
- Rouge1: 29.7694
- Rouge2: 15.6776
- Rougel: 27.3556
- Rougelsum: 28.4819
- Gen Len: 19.0

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.9943        | 1.0   | 170  | 2.2042          | 28.1135 | 13.7477 | 25.4842 | 26.6467   | 18.9768 |
| 2.7955        | 2.0   | 340  | 2.1561          | 28.5159 | 14.3492 | 26.0596 | 27.2431   | 18.9853 |
| 2.6378        | 3.0   | 510  | 2.1310          | 28.9554 | 14.6901 | 26.4208 | 27.5523   | 18.9915 |
| 2.5962        | 4.0   | 680  | 2.1110          | 29.381  | 15.1503 | 26.8406 | 27.9653   | 18.9915 |
| 2.5369        | 5.0   | 850  | 2.1020          | 29.5767 | 15.2692 | 27.0113 | 28.1849   | 18.9963 |
| 2.5103        | 6.0   | 1020 | 2.0907          | 29.6354 | 15.434  | 27.0893 | 28.2703   | 18.9963 |
| 2.4524        | 7.0   | 1190 | 2.0840          | 29.7812 | 15.4963 | 27.2779 | 28.385    | 18.9963 |
| 2.4472        | 8.0   | 1360 | 2.0800          | 29.6011 | 15.5138 | 27.1381 | 28.2799   | 18.9963 |
| 2.4089        | 9.0   | 1530 | 2.0752          | 29.7647 | 15.6183 | 27.318  | 28.4747   | 18.9963 |
| 2.4011        | 10.0  | 1700 | 2.0710          | 29.6533 | 15.5536 | 27.2687 | 28.4457   | 19.0    |
| 2.3792        | 11.0  | 1870 | 2.0656          | 29.8668 | 15.6931 | 27.4208 | 28.5477   | 19.0    |
| 2.3588        | 12.0  | 2040 | 2.0635          | 29.8378 | 15.682  | 27.4635 | 28.5803   | 18.9963 |
| 2.3397        | 13.0  | 2210 | 2.0630          | 29.9043 | 15.7535 | 27.5065 | 28.6539   | 19.0    |
| 2.3201        | 14.0  | 2380 | 2.0600          | 29.7926 | 15.7077 | 27.4066 | 28.5302   | 18.9963 |
| 2.3241        | 15.0  | 2550 | 2.0615          | 29.8536 | 15.7929 | 27.4572 | 28.5704   | 19.0    |
| 2.3183        | 16.0  | 2720 | 2.0574          | 29.7529 | 15.6729 | 27.3388 | 28.4678   | 19.0    |
| 2.3346        | 17.0  | 2890 | 2.0571          | 29.7443 | 15.6459 | 27.3245 | 28.4549   | 19.0    |
| 2.2932        | 18.0  | 3060 | 2.0577          | 29.7467 | 15.6717 | 27.3391 | 28.4541   | 19.0    |
| 2.2755        | 19.0  | 3230 | 2.0574          | 29.7694 | 15.6776 | 27.3556 | 28.4819   | 19.0    |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "inference": {"parameters": {"max_length": 160}}, "model-index": [{"name": "t5-base-snl", "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 

t5-base-snl
===========


This model is a fine-tuned version of north/t5\_base\_NCC\_lm on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0574
* Rouge1: 29.7694
* Rouge2: 15.6776
* Rougel: 27.3556
* Rougelsum: 28.4819
* Gen Len: 19.0


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: 4
* eval\_batch\_size: 4
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0


### Training results



### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2
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: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0 ### Training results ### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2
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: 5e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* distributed\_type: multi-GPU
* num\_devices: 4
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* total\_eval\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0### Training results### Framework versions


* Transformers 4.27.0.dev0
* Pytorch 1.13.1
* Datasets 2.10.1
* Tokenizers 0.13.2