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Cil Ordinal Coral Seed3

This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set: Loss: 0.3482 Mae: 0.4476 Coral Mae: 0.5951 Rounded Mae: 0.3903 Accuracy: 0.5135

KindLoRABase modelxlm-roberta-baseVersionadapter_modelPublisher@MichaHenhCgrade

Model source

Kind
LoRA
File size
46.2 MB
Base model
xlm-roberta-base
Version
vadapter_model
Updated
Oct 3, 2026
Publisher
@MichaHenh
Downloads
3
Source
Hugging Face

Source description

cil-ordinal-coral-seed3

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

  • Loss: 0.3482
  • Mae: 0.4476
  • Coral Mae: 0.5951
  • Rounded Mae: 0.3903
  • Accuracy: 0.5135

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: 0.00015
  • train_batch_size: 64
  • eval_batch_size: 1024
  • seed: 3
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossMaeCoral MaeRounded MaeAccuracy
0.51830.14115000.47110.55560.88260.49960.4046
0.45810.282210000.44830.49830.83920.44290.4150
0.44210.423315000.42990.48630.79420.42910.4306
0.42530.564320000.41810.49940.74900.43170.4476
0.41420.705425000.40740.48460.74460.41920.4496
0.40430.846530000.39750.47020.69250.40860.4694
0.39510.987635000.38770.47150.69210.40310.4685
0.38371.128740000.38220.46670.65320.40880.4870
0.37561.269845000.37350.47490.64860.40760.4881
0.37021.410850000.36820.46120.62840.40050.4973
0.36401.551955000.36310.46100.61940.39790.5025
0.36401.693060000.35880.46070.62240.39630.5001
0.35481.834165000.35690.46260.63690.39560.4929
0.35521.975270000.35420.45210.59850.39440.5122
0.34932.116375000.35350.45040.60460.39310.5090
0.34632.257380000.35470.44430.61050.39430.5063
0.34422.398485000.35080.44590.59540.39030.5135
0.34332.539590000.34870.44830.59440.39100.5140
0.34152.680695000.34860.44680.59590.39030.5130
0.34302.8217100000.34820.44800.59490.39070.5131
0.34352.9628105000.34820.44760.59520.39050.5135
0.34353.0106320.34820.44760.59510.39030.5135

Framework versions

  • PEFT 0.19.1
  • Transformers 5.8.1
  • Pytorch 2.11.0+cu128
  • Datasets 4.8.5
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrimaryVersion 1902554814cf480658f8bf050b2164082765171a
huggingface.co/MichaHenh/cil-ordinal-coral-seed3/tree/1902554814cf480658f8bf050b2164082765171a

Verified Oct 3

Model artifacts

1 artifact

adapter_model.safetensors

safetensors · 46.2 MB · SHA-256 cbe75d4f3001…349a · Hugging Face

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Source excerpts

3 excerpts

--- library_name: peft license: mit base_model: xlm-roberta-base tags: - base_model:adapter:xlm-roberta-base - lora - transformers metrics: - accuracy model-index: - name: cil-ordinal-coral-seed3 results: [] --- <!-- 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. --> # cil-ordinal-coral-seed3 This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3482 - Mae: 0.4476 - Coral Mae: 0.5951 - Rounded Mae: 0.3903 - Accuracy: 0.5135 ## 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: 0.00015 - train_batch_size: 64 - eval_batch_size: 1024 - seed: 3 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 100 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Mae | Coral Mae | Rounded Mae | Accuracy | |:-------------:|:------:|:-----:|:---------------:|:------:|:---------:|:-----------:|:--------:| | 0.5183 | 0.1411 | 500 | 0.4711 | 0.5556 | 0.8826 | 0.4996 | 0.4046 | | 0.4581 | 0.2822 | 1000 | 0.4483 | 0.4983 | 0.8392 | 0.4429 | 0.4150 | | 0.4421 | 0.4233 | 1500 | 0.4299 | 0.4863 | 0.7942 | 0.4291 | 0.4306 | | 0.4253 | 0.5643 | 2000 | 0.4181 | 0.4994 | 0.7490 | 0.4317 | 0.4476 | | 0.4142 | 0.7054 | 2500 | 0.4074 | 0.4846 | 0.7446 | 0.4192 | 0.4496 | | 0.4043 | 0.8465 | 3000 | 0.3975 | 0.4702 | 0.6925 | 0.4086 | 0.4694 | | 0.3951 | 0.9876 | 3500 | 0.3877 | 0.4715 | 0.6921 | 0.4031 | 0.4685 | | 0.3837 | 1.1287 | 4000 | 0.3822 | 0.4667 | 0.6532 | 0.4088 | 0.4870 | | 0.3756 | 1.2698 | 4500 | 0.3735 | 0.4749 | 0.6486 | 0.4076 | 0.4881 | | 0.3702 | 1.4108 | 5000 | 0.3682 | 0.4612 | 0.6284 | 0.4005 | 0.4973 | | 0.3640 | 1.5519 | 5500 | 0.3631 | 0.4610 | 0.6194 | 0.3979 | 0.5025 | | 0.3640 | 1.6930 | 6000 | 0.3588 | 0.4607 | 0.6224 | 0.3963 | 0.5001 | | 0.3548...

Source context: 3 downloads · 0 likes · Library peft · Repo MichaHenh/cil-ordinal-coral-seed3

Source context: 1 downloads · 0 likes · Library peft · Repo MichaHenh/cil-ordinal-coral-seed3