mt5-small-task2-dataset2

This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4320
  • Accuracy: 0.37

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: 5.6e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
7.018 1.0 250 1.2234 0.014
1.6684 2.0 500 0.8157 0.124
1.0289 3.0 750 0.6527 0.222
0.8021 4.0 1000 0.5877 0.282
0.6964 5.0 1250 0.5360 0.3
0.6252 6.0 1500 0.5118 0.32
0.5828 7.0 1750 0.4899 0.318
0.5436 8.0 2000 0.4718 0.35
0.5232 9.0 2250 0.4625 0.34
0.5005 10.0 2500 0.4556 0.342
0.4789 11.0 2750 0.4436 0.356
0.4733 12.0 3000 0.4379 0.356
0.4651 13.0 3250 0.4347 0.366
0.4591 14.0 3500 0.4320 0.37
0.4508 15.0 3750 0.4320 0.37

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Tokenizers 0.15.0
Downloads last month
24
Safetensors
Model size
300M 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 ZhiguangHan/mt5-small-task2-dataset2

Base model

google/mt5-small
Finetuned
(370)
this model