Hugging Face's logo

shanhy
/
xlm-roberta-base_latin_kin-amh-eng_train_spearman_corr

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
xlm-roberta-base_latin_kin-amh-eng_train_spearman_corr / README.md
shanhy's picture
shanhy
End of training
2620faf verified
preview code
|
raw
history blame contribute delete
3.03 kB
metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
  - generated_from_trainer
model-index:
  - name: xlm-roberta-base_latin_kin-amh-eng_train_spearman_corr
    results: []

xlm-roberta-base_latin_kin-amh-eng_train_spearman_corr

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

  • Loss: 0.0290
  • Spearman Corr: 0.7237

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: 2e-05
  • train_batch_size: 32
  • eval_batch_size: 128
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Spearman Corr
No log 0.59 200 0.0279 0.6205
No log 1.17 400 0.0265 0.6575
No log 1.76 600 0.0380 0.6844
0.0373 2.35 800 0.0307 0.7164
0.0373 2.93 1000 0.0340 0.6776
0.0373 3.52 1200 0.0312 0.7050
0.0244 4.11 1400 0.0298 0.7134
0.0244 4.69 1600 0.0285 0.7190
0.0244 5.28 1800 0.0278 0.7217
0.0244 5.87 2000 0.0298 0.7006
0.0185 6.45 2200 0.0258 0.7114
0.0185 7.04 2400 0.0295 0.7164
0.0185 7.62 2600 0.0333 0.7204
0.0144 8.21 2800 0.0300 0.7201
0.0144 8.8 3000 0.0326 0.7290
0.0144 9.38 3200 0.0292 0.7114
0.0144 9.97 3400 0.0289 0.7052
0.0109 10.56 3600 0.0336 0.7125
0.0109 11.14 3800 0.0307 0.7147
0.0109 11.73 4000 0.0308 0.7174
0.0086 12.32 4200 0.0285 0.7217
0.0086 12.9 4400 0.0288 0.7083
0.0086 13.49 4600 0.0290 0.7237

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2