t5-mlsum_2
This model is a fine-tuned version of Kafaite24/t5-mlsum_2 on the mlsum 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cpu
- Datasets 2.8.0
- Tokenizers 0.13.2
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Kafaite24/t5-mlsum_2") model = AutoModelForSeq2SeqLM.from_pretrained("Kafaite24/t5-mlsum_2")