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TwitchLeagueBert-1000k-finetuned-highlight-detection
This model is a fine-tuned version of Epidot/TwitchLeagueBert-1000k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1146
- Precision: 0.4420
- F1: 0.3977
- Recall: 0.3614
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | F1 | Recall |
|---|---|---|---|---|---|---|
| 0.0205 | 1.04 | 20000 | 0.1119 | 0.4665 | 0.4689 | 0.4712 |
| 0.0091 | 2.09 | 40000 | 0.1086 | 0.4803 | 0.4447 | 0.4139 |
| 0.0062 | 3.13 | 60000 | 0.1172 | 0.4382 | 0.4192 | 0.4018 |
| 0.0038 | 4.18 | 80000 | 0.1146 | 0.4420 | 0.3977 | 0.3614 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.7.1
- Datasets 2.0.0
- Tokenizers 0.12.1
