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question_generation_final
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0602
- eval_runtime: 301.5563
- eval_samples_per_second: 35.051
- eval_steps_per_second: 2.192
- epoch: 0.64
- step: 3500
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for nadika/question_generation_final
Base model
google-t5/t5-small
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nadika/question_generation_final") model = AutoModelForSeq2SeqLM.from_pretrained("nadika/question_generation_final", device_map="auto")