metadata

license: mit
base_model: cointegrated/rut5-base-multitask
tags:
  - generated_from_trainer
model-index:
  - name: finetune_t5_base_only_hack
    results: []

finetune_t5_base_only_hack

This model is a fine-tuned version of cointegrated/rut5-base-multitask on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.4584

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: 0.0004
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 32
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss
1.8215	3.86	150	1.5392
1.579	7.72	300	1.4584

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.15.0
Tokenizers 0.15.0