yohannesahunm/amharic_text_summarization

<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->

amharictextsummarization

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

• —eval_loss: 1.8555
• —eval_rouge1: 18.0073
• —eval_rouge2: 10.0967
• —eval_rougeL: 17.7031
• —eval_rougeLsum: 17.704
• —eval_runtime: 364.1187
• —evalsamplesper_second: 14.207
• —evalstepsper_second: 1.777
• —epoch: 8.0
• —step: 20736

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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 8

Framework versions

• —Transformers 4.35.2
• —Pytorch 2.1.0+cu121
• —Datasets 2.16.1
• —Tokenizers 0.15.0