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")