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# flan-t5-small-taboo-for-llms-deft

This model is a fine-tuned version of [vlkn/flan-t5-small-taboo-for-llms-deft](https://huggingface.co/vlkn/flan-t5-small-taboo-for-llms-deft) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2875
- Rouge1: 32.1845
- Rouge2: 16.9705
- Rougel: 29.529
- Rougelsum: 29.6072
- Gen Len: 15.2997

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.4309        | 0.62  | 100  | 2.3010          | 31.469  | 16.5456 | 28.6201 | 28.6762   | 15.4739 |
| 2.619         | 1.24  | 200  | 2.2973          | 31.933  | 16.7494 | 29.1285 | 29.238    | 15.4983 |
| 2.6097        | 1.85  | 300  | 2.2928          | 32.2705 | 16.9959 | 29.6145 | 29.7188   | 15.2927 |
| 2.5818        | 2.47  | 400  | 2.2880          | 32.1637 | 16.7922 | 29.543  | 29.5852   | 15.4564 |
| 2.5782        | 3.09  | 500  | 2.2875          | 32.1845 | 16.9705 | 29.529  | 29.6072   | 15.2997 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "flan-t5-small-taboo-for-llms-deft", "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 

flan-t5-small-taboo-for-llms-deft
=================================


This model is a fine-tuned version of vlkn/flan-t5-small-taboo-for-llms-deft on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.2875
* Rouge1: 32.1845
* Rouge2: 16.9705
* Rougel: 29.529
* Rougelsum: 29.6072
* Gen Len: 15.2997


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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 500


### Training results



### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 500 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
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: 0.0001
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* training\_steps: 500 ### Training results ### Framework versions


* Transformers 4.29.2
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3