Edit model card

finetune_t5_base_hack_prefix

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

  • Loss: 1.4665

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
1.8806 3.86 150 1.5554
1.6185 7.72 300 1.4665

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
Downloads last month
5
Safetensors
Model size
244M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for rhythm00/finetune-rut5-base-comments

Finetuned
(2)
this model