xlm-roberta-base_latin_original_amh-hau-eng_train_loss
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: 0.0269
- Spearman Corr: 0.7656
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 | 1.55 | 200 | 0.0252 | 0.7541 |
0.0498 | 3.1 | 400 | 0.0263 | 0.7765 |
0.0243 | 4.65 | 600 | 0.0245 | 0.7840 |
0.019 | 6.2 | 800 | 0.0235 | 0.7867 |
0.019 | 7.75 | 1000 | 0.0335 | 0.7707 |
0.0147 | 9.3 | 1200 | 0.0297 | 0.7705 |
0.0118 | 10.85 | 1400 | 0.0267 | 0.7764 |
0.0096 | 12.4 | 1600 | 0.0276 | 0.7745 |
0.0078 | 13.95 | 1800 | 0.0278 | 0.7631 |
0.0078 | 15.5 | 2000 | 0.0288 | 0.7699 |
0.0067 | 17.05 | 2200 | 0.0249 | 0.7616 |
0.0062 | 18.6 | 2400 | 0.0269 | 0.7656 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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