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# t5-small-e-snli-generation-label_and_explanation-selected-b64

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the esnli dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9257
- Accuracy: 0.8733
- F1: 0.8730
- Bertscore F1: 0.9356
- Rouge1: 0.6144
- Rouge2: 0.4096
- Rougel: 0.5592
- Rougelsum: 0.5611
- Bleu: 0.4224

## 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: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Bertscore F1 | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu   |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------------:|:------:|:------:|:------:|:---------:|:------:|
| 1.6638        | 0.23  | 2000  | 2.0039          | 0.7883   | 0.7869 | 0.9274       | 0.5705 | 0.3601 | 0.5175 | 0.5192    | 0.3730 |
| 1.2998        | 0.47  | 4000  | 1.9378          | 0.8283   | 0.8293 | 0.9303       | 0.5861 | 0.3748 | 0.5310 | 0.5329    | 0.3854 |
| 1.2351        | 0.7   | 6000  | 1.8752          | 0.8431   | 0.8437 | 0.9321       | 0.5951 | 0.3880 | 0.5411 | 0.5430    | 0.3954 |
| 1.1948        | 0.93  | 8000  | 1.9346          | 0.8536   | 0.8529 | 0.9333       | 0.6018 | 0.3931 | 0.5451 | 0.5472    | 0.4006 |
| 1.1537        | 1.16  | 10000 | 1.8881          | 0.8654   | 0.8647 | 0.9332       | 0.6070 | 0.4023 | 0.5483 | 0.5506    | 0.4096 |
| 1.1298        | 1.4   | 12000 | 1.9265          | 0.8690   | 0.8685 | 0.9337       | 0.6053 | 0.3988 | 0.5507 | 0.5526    | 0.4093 |
| 1.1219        | 1.63  | 14000 | 1.9017          | 0.8713   | 0.8714 | 0.9332       | 0.6029 | 0.3941 | 0.5470 | 0.5489    | 0.4042 |
| 1.1088        | 1.86  | 16000 | 1.9257          | 0.8733   | 0.8730 | 0.9356       | 0.6144 | 0.4096 | 0.5592 | 0.5611    | 0.4224 |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["esnli"], "metrics": ["accuracy", "f1", "rouge", "bleu"], "model-index": [{"name": "t5-small-e-snli-generation-label_and_explanation-selected-b64", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "esnli", "type": "esnli", "config": "plain_text", "split": "validation", "args": "plain_text"}, "metrics": [{"type": "accuracy", "value": 0.8732981101402154, "name": "Accuracy"}, {"type": "f1", "value": 0.8729633394714756, "name": "F1"}, {"type": "rouge", "value": 0.6144211309547953, "name": "Rouge1"}, {"type": "bleu", "value": 0.4223746159966924, "name": "Bleu"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:esnli license:apache-2.0 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-esnli #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

t5-small-e-snli-generation-label\_and\_explanation-selected-b64
===============================================================


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


* Loss: 1.9257
* Accuracy: 0.8733
* F1: 0.8730
* Bertscore F1: 0.9356
* Rouge1: 0.6144
* Rouge2: 0.4096
* Rougel: 0.5592
* Rougelsum: 0.5611
* Bleu: 0.4224


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: 0.001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-esnli #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-esnli #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.001
* train\_batch\_size: 64
* eval\_batch\_size: 64
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_ratio: 0.05
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0+cu117
* Datasets 2.11.0
* Tokenizers 0.13.2