| activations: Tanh | |
| batch_size: 4 | |
| class_identifier: unified_metric | |
| cross_entropy_weights: null | |
| dropout: 0.1 | |
| encoder_learning_rate: 1.0e-06 | |
| encoder_model: XLM-RoBERTa | |
| error_labels: | |
| - minor | |
| - major | |
| final_activation: null | |
| hidden_sizes: | |
| - 3072 | |
| - 1024 | |
| input_segments: | |
| - mt | |
| - src | |
| - ref | |
| keep_embeddings_frozen: true | |
| layer: mix | |
| layer_norm: false | |
| layer_transformation: sparsemax | |
| layerwise_decay: 0.95 | |
| learning_rate: 1.5e-05 | |
| load_pretrained_weights: true | |
| loss: mse | |
| loss_lambda: 0.65 | |
| nr_frozen_epochs: 0.3 | |
| optimizer: AdamW | |
| pool: avg | |
| pretrained_model: microsoft/infoxlm-large | |
| sent_layer: mix | |
| train_data: | |
| - data/wmt-human-eval/reward_dataset.csv | |
| validation_data: 0.1 | |
| warmup_steps: 0 | |
| word_layer: 24 | |
| word_level_training: false | |
| min_zscore: -1.8359497445108464 | |
| max_zscore: 0.8327298628095561 | |