xlm-roberta-base_original_esp-kin-eng_train
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: 0.0301
- Spearman Corr: 0.7160
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 |
1.63 |
200 |
0.0292 |
0.6299 |
0.0375 |
3.27 |
400 |
0.0290 |
0.6845 |
0.0212 |
4.9 |
600 |
0.0259 |
0.6877 |
0.0164 |
6.53 |
800 |
0.0287 |
0.7094 |
0.0127 |
8.16 |
1000 |
0.0285 |
0.7219 |
0.0127 |
9.8 |
1200 |
0.0318 |
0.7103 |
0.0102 |
11.43 |
1400 |
0.0299 |
0.7125 |
0.008 |
13.06 |
1600 |
0.0357 |
0.7183 |
0.0067 |
14.69 |
1800 |
0.0282 |
0.7207 |
0.0056 |
16.33 |
2000 |
0.0314 |
0.7154 |
0.0056 |
17.96 |
2200 |
0.0317 |
0.7145 |
0.0049 |
19.59 |
2400 |
0.0302 |
0.7111 |
0.0044 |
21.22 |
2600 |
0.0301 |
0.7160 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2