metadata
library_name: transformers
license: apache-2.0
base_model: google/bigbird-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FNetHateSpeechClassification
results: []
FNetHateSpeechClassification
This model is a fine-tuned version of google/bigbird-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.4802
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: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6965 | 1.0 | 1137 | 0.6932 | 0.4802 |
| 0.6943 | 2.0 | 2274 | 0.6927 | 0.5198 |
| 0.6949 | 3.0 | 3411 | 0.6949 | 0.4802 |
| 0.6941 | 4.0 | 4548 | 0.6936 | 0.4802 |
| 0.6939 | 5.0 | 5685 | 0.6926 | 0.5198 |
| 0.6937 | 6.0 | 6822 | 0.6926 | 0.5198 |
| 0.6937 | 7.0 | 7959 | 0.6935 | 0.4802 |
| 0.694 | 8.0 | 9096 | 0.6936 | 0.4802 |
| 0.6934 | 9.0 | 10233 | 0.6932 | 0.4802 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0