Flan_t5_Large_Chat_Summary
This model is a fine-tuned version of google/flan-t5-large on the shared_TaskA dataset.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Example Uses
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer_pre = AutoTokenizer.from_pretrained("Amalq/flan_t5_large_chat_summary")
model_pre = AutoModelForSeq2SeqLM.from_pretrained("Amalq/flan_t5_large_chat_summary")