metadata
license: mit
base_model: LIAMF-USP/roberta-large-finetuned-race
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bigbird-roberta-large
results: []
bigbird-roberta-large
This model is a fine-tuned version of LIAMF-USP/roberta-large-finetuned-race on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6094
- Accuracy: 0.1976
- F1: 0.1757
- Precision: 0.1893
- Recall: 0.1911
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: 8
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|
| 1.6272 | 0.3233 | 1200 | 1.6094 | 0.2082 | 0.1431 | 0.2007 | 0.1996 |
| 1.6218 | 0.6466 | 2400 | 1.6094 | 0.2117 | 0.1340 | 0.1876 | 0.1998 |
| 1.6235 | 0.9698 | 3600 | 1.6094 | 0.2104 | 0.1752 | 0.2005 | 0.2015 |
| 1.617 | 1.2931 | 4800 | 1.6094 | 0.2088 | 0.1956 | 0.2037 | 0.2028 |
| 1.61 | 1.6164 | 6000 | 1.6094 | 0.2091 | 0.1606 | 0.2127 | 0.2024 |
| 1.6126 | 1.9397 | 7200 | 1.6094 | 0.2108 | 0.1796 | 0.1965 | 0.2011 |
| 1.6174 | 2.2629 | 8400 | 1.6094 | 0.2095 | 0.1833 | 0.2036 | 0.2024 |
| 1.6125 | 2.5862 | 9600 | 1.6094 | 0.2097 | 0.1847 | 0.1963 | 0.2016 |
| 1.6192 | 2.9095 | 10800 | 1.6094 | 0.1976 | 0.1757 | 0.1893 | 0.1911 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1