CoolFace
Modelpublic

Angelectronic/gemma-QA-ViMMRC-Squad-v1.1

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
0likes4downloads
Model Card

<!-- 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. -->

gemma-QA-ViMMRC-Squad-v1.1

This model is a fine-tuned version of unsloth/gemma-1.1-7b-it-bnb-4bit on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 3.3372

Model description

More information needed

Intended uses & limitations

  • —Prompt 1: Given the following reference, create a question and a corresponding answer to the question: + [context]
  • —Prompt 2: Given the following reference, create a multiple-choice question and its corresponding answer: + [context]

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • —learning_rate: 0.0002
  • —trainbatchsize: 16
  • —evalbatchsize: 8
  • —seed: 3407
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 64
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 5
  • —num_epochs: 3

Training results

Training LossEpochStepValidation Loss
0.80.23073201.9584
0.40310.46146402.0371
0.40.69219602.1358
0.40.922912802.2552
0.23281.153616002.4241
0.21.384319202.5637
0.21.615022402.7250
0.11171.845725602.8899
0.10082.076428803.1551
0.05782.307132003.2185
0.05662.537935203.3025
0.05552.768638403.3309
0.05162.999341603.3372

Framework versions

  • —PEFT 0.10.0
  • —Transformers 4.40.2
  • —Pytorch 2.3.0
  • —Datasets 2.19.1
  • —Tokenizers 0.19.1