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metadata
base_model: yihongLiu/furina
tags:
  - generated_from_trainer
model-index:
  - name: furina_seed42_eng_esp_kin
    results: []

furina_seed42_eng_esp_kin

This model is a fine-tuned version of yihongLiu/furina on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0131
  • Spearman Corr: 0.8588

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 0.6 200 0.0342 0.6070
No log 1.21 400 0.0245 0.6934
No log 1.81 600 0.0230 0.7199
0.0458 2.42 800 0.0215 0.7448
0.0458 3.02 1000 0.0203 0.7510
0.0458 3.63 1200 0.0198 0.7712
0.02 4.23 1400 0.0180 0.7809
0.02 4.83 1600 0.0191 0.7812
0.02 5.44 1800 0.0182 0.7921
0.0142 6.04 2000 0.0177 0.8010
0.0142 6.65 2200 0.0170 0.8004
0.0142 7.25 2400 0.0159 0.8085
0.0142 7.85 2600 0.0161 0.8114
0.01 8.46 2800 0.0160 0.8142
0.01 9.06 3000 0.0152 0.8218
0.01 9.67 3200 0.0157 0.8234
0.0072 10.27 3400 0.0145 0.8303
0.0072 10.88 3600 0.0153 0.8311
0.0072 11.48 3800 0.0147 0.8311
0.0059 12.08 4000 0.0140 0.8373
0.0059 12.69 4200 0.0139 0.8401
0.0059 13.29 4400 0.0143 0.8406
0.0059 13.9 4600 0.0136 0.8447
0.0049 14.5 4800 0.0140 0.8453
0.0049 15.11 5000 0.0133 0.8452
0.0049 15.71 5200 0.0140 0.8450
0.0041 16.31 5400 0.0135 0.8481
0.0041 16.92 5600 0.0147 0.8489
0.0041 17.52 5800 0.0135 0.8492
0.0037 18.13 6000 0.0134 0.8498
0.0037 18.73 6200 0.0131 0.8492
0.0037 19.34 6400 0.0134 0.8524
0.0037 19.94 6600 0.0134 0.8536
0.0034 20.54 6800 0.0128 0.8540
0.0034 21.15 7000 0.0134 0.8539
0.0034 21.75 7200 0.0138 0.8531
0.0031 22.36 7400 0.0125 0.8562
0.0031 22.96 7600 0.0135 0.8585
0.0031 23.56 7800 0.0132 0.8569
0.0028 24.17 8000 0.0126 0.8564
0.0028 24.77 8200 0.0130 0.8574
0.0028 25.38 8400 0.0128 0.8587
0.0026 25.98 8600 0.0128 0.8595
0.0026 26.59 8800 0.0131 0.8582
0.0026 27.19 9000 0.0131 0.8588

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1