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# rob2rand_chen_w_prefix_c_fc

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0939
- eval_bleu: 84.4530
- eval_em: 52.0156
- eval_bleu_em: 68.2343
- eval_runtime: 21.0016
- eval_samples_per_second: 36.616
- eval_steps_per_second: 0.619
- step: 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-06
- 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_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.18.0
- Pytorch 1.7.1
- Datasets 2.1.0
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "model-index": [{"name": "rob2rand_chen_w_prefix_c_fc", "results": []}]}
transformers pytorch encoder-decoder text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #encoder-decoder #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# rob2rand_chen_w_prefix_c_fc

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0939
- eval_bleu: 84.4530
- eval_em: 52.0156
- eval_bleu_em: 68.2343
- eval_runtime: 21.0016
- eval_samples_per_second: 36.616
- eval_steps_per_second: 0.619
- step: 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-06
- 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_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.18.0
- Pytorch 1.7.1
- Datasets 2.1.0
- Tokenizers 0.12.1

# rob2rand_chen_w_prefix_c_fc

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0939
- eval_bleu: 84.4530
- eval_em: 52.0156
- eval_bleu_em: 68.2343
- eval_runtime: 21.0016
- eval_samples_per_second: 36.616
- eval_steps_per_second: 0.619
- step: 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-06
- 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_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.18.0
- Pytorch 1.7.1
- Datasets 2.1.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #encoder-decoder #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # rob2rand_chen_w_prefix_c_fc

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0939
- eval_bleu: 84.4530
- eval_em: 52.0156
- eval_bleu_em: 68.2343
- eval_runtime: 21.0016
- eval_samples_per_second: 36.616
- eval_steps_per_second: 0.619
- step: 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-06
- 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_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.18.0
- Pytorch 1.7.1
- Datasets 2.1.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #encoder-decoder #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# rob2rand_chen_w_prefix_c_fc

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.0939
- eval_bleu: 84.4530
- eval_em: 52.0156
- eval_bleu_em: 68.2343
- eval_runtime: 21.0016
- eval_samples_per_second: 36.616
- eval_steps_per_second: 0.619
- step: 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-06
- 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_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.18.0
- Pytorch 1.7.1
- Datasets 2.1.0
- Tokenizers 0.12.1