metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-large-finetuned-race
results: []
roberta-large-finetuned-race
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5249
- Accuracy: 0.3094
- F1: 0.3011
- Precision: 0.3292
- Recall: 0.3011
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: 28
- eval_batch_size: 28
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.5519 | 1.1310 | 1200 | 1.5674 | 0.2998 | 0.2964 | 0.3018 | 0.2954 |
| 1.5254 | 2.2620 | 2400 | 1.5249 | 0.3094 | 0.3011 | 0.3292 | 0.3011 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1