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roberta-large-go-emotions-2
This model is a fine-tuned version of roberta-large on the go_emotions dataset. It achieves the following results on the test set (with a threshold of 0.15):
- Accuracy: 0.44020
- Precision: 0.5041
- Recall: 0.5461
- F1: 0.5180
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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
Training results
| Training Loss | Epoch | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 0.0889 | 0.4043 | 0.4807 | 0.4568 | 0.4446 |
| 0.1062 | 2.0 | 0.0828 | 0.4113 | 0.4608 | 0.5363 | 0.4868 |
| 0.1062 | 3.0 | 0.0813 | 0.4201 | 0.5198 | 0.5612 | 0.5227 |
| No log | 4.0 | 0.0862 | 0.4292 | 0.5012 | 0.5558 | 0.5208 |
| 0.0597 | 5.0 | 0.0924 | 0.4329 | 0.5164 | 0.5362 | 0.5151 |
| 0.0597 | 6.0 | 0.0956 | 0.4445 | 0.5241 | 0.5328 | 0.5161 |
| No log | 7.0 | 0.0962 | 0.4648 | 0.5138 | 0.5277 | 0.5151 |
| 0.0458 | 8.0 | 0.0962 | 0.4462 | 0.5257 | 0.5270 | 0.5203 |
| 0.0458 | 9.0 | 0.1029 | 0.4432 | 0.5076 | 0.5249 | 0.5111 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1
