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# t5-skills

This model is a fine-tuned version of [flozi00/t5-skills](https://huggingface.co/flozi00/t5-skills) on the None dataset.

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results



### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.14.0
- Tokenizers 0.10.2

{"tags": ["generated_from_trainer"], "model-index": [{"name": "t5-skills", "results": []}]}
transformers pytorch tensorboard safetensors t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# t5-skills

This model is a fine-tuned version of flozi00/t5-skills on the None dataset.

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results



### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.14.0
- Tokenizers 0.10.2

# t5-skills

This model is a fine-tuned version of flozi00/t5-skills on the None dataset. ## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0 ### Training results ### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.14.0
- Tokenizers 0.10.2
TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # t5-skills

This model is a fine-tuned version of flozi00/t5-skills on the None dataset. ## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0 ### Training results ### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.14.0
- Tokenizers 0.10.2
passage: TAGS
#transformers #pytorch #tensorboard #safetensors #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# t5-skills

This model is a fine-tuned version of flozi00/t5-skills on the None dataset.## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0### Training results### Framework versions

- Transformers 4.12.5
- Pytorch 1.8.1
- Datasets 1.14.0
- Tokenizers 0.10.2