metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: xlm-roberta-base_afr_corr_0.0001
results: []
xlm-roberta-base_afr_corr_0.0001
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: 0.0461
- Spearman Corr: -0.0407
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: 0.0001
- 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 | 0.85 | 200 | 0.0466 | 0.1403 |
| No log | 1.69 | 400 | 0.0463 | nan |
| 0.0564 | 2.54 | 600 | 0.0476 | -0.0126 |
| 0.0564 | 3.38 | 800 | 0.0463 | nan |
| 0.0519 | 4.23 | 1000 | 0.0481 | -0.0333 |
| 0.0519 | 5.07 | 1200 | 0.0463 | -0.1378 |
| 0.0519 | 5.92 | 1400 | 0.0480 | -0.0688 |
| 0.051 | 6.77 | 1600 | 0.0463 | nan |
| 0.051 | 7.61 | 1800 | 0.0461 | -0.0407 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2