CoolFace
Modelpublic

haryoaw/scenario-TCR-XLMV_data-cl-cardiff_cl_only_delta2

sourceHugging Facemitupdated 2y agoView on Hugging Face
0likes12downloads
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. -->

scenario-TCR-XLMVdata-cl-cardiffclonlydelta2

This model is a fine-tuned version of facebook/xlm-v-base on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.0986
  • —Accuracy: 0.3333
  • —F1: 0.1667

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: 5e-05
  • —trainbatchsize: 32
  • —evalbatchsize: 32
  • —seed: 2
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 30

Training results

Training LossEpochStepValidation LossAccuracyF1
No log1.092501.09870.33410.1684
1.09962.175001.09940.33330.1667
1.09963.267501.09880.33330.1667
1.09984.3510001.09870.33330.1667
1.09985.4312501.10010.33330.1667
1.10016.5215001.09860.33330.1667
1.10017.6117501.09880.33330.1667
1.09948.720001.09880.33330.1667
1.09949.7822501.10480.33330.1667
1.099810.8725001.09880.33330.1667
1.099811.9627501.09870.33330.1667
1.100113.0430001.09860.33330.1667
1.100114.1332501.09890.33330.1667
1.099415.2235001.09910.33330.1667
1.099416.337501.09870.33330.1667
1.098917.3940001.09890.33330.1667
1.098918.4842501.09880.33330.1667
1.099119.5745001.09880.33330.1667
1.099120.6547501.09880.33330.1667
1.099221.7450001.09880.33330.1667
1.099222.8352501.09860.33330.1667
1.099123.9155001.09860.33330.1667
1.099125.057501.09870.33330.1667
1.098926.0960001.09860.33330.1667
1.098927.1762501.09860.33330.1667
1.099128.2665001.09860.33330.1667
1.099129.3567501.09860.33330.1667

Framework versions

  • —Transformers 4.33.3
  • —Pytorch 2.1.1+cu121
  • —Datasets 2.14.5
  • —Tokenizers 0.13.3