scenario-kd-from-scratch-gold-silver-data-tweet_eval-sentiment-model-xlm-roberta
This model is a fine-tuned version of xlm-roberta-base on the tweet_eval dataset. It achieves the following results on the evaluation set:
- Loss: 3.0720
- Accuracy: 0.6755
- F1: 0.6420
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: 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: 6969
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
4.3095 | 0.7 | 1000 | 3.4542 | 0.638 | 0.5615 |
3.1112 | 1.4 | 2000 | 3.0357 | 0.682 | 0.6484 |
2.8791 | 2.1 | 3000 | 2.9641 | 0.677 | 0.6373 |
2.5821 | 2.81 | 4000 | 3.0110 | 0.6695 | 0.6303 |
2.1895 | 3.51 | 5000 | 3.0888 | 0.672 | 0.6542 |
1.9976 | 4.21 | 6000 | 3.1685 | 0.677 | 0.6447 |
1.918 | 4.91 | 7000 | 3.1264 | 0.6715 | 0.6543 |
1.6104 | 5.61 | 8000 | 2.9487 | 0.6715 | 0.6396 |
1.3811 | 6.31 | 9000 | 3.5539 | 0.6555 | 0.6384 |
1.4193 | 7.01 | 10000 | 3.1164 | 0.661 | 0.6316 |
1.2829 | 7.71 | 11000 | 3.0770 | 0.681 | 0.6506 |
1.132 | 8.42 | 12000 | 3.0204 | 0.672 | 0.6428 |
1.1429 | 9.12 | 13000 | 2.9914 | 0.6635 | 0.6289 |
1.0642 | 9.82 | 14000 | 3.0322 | 0.668 | 0.6422 |
0.9858 | 10.52 | 15000 | 3.0235 | 0.664 | 0.6180 |
0.934 | 11.22 | 16000 | 2.9512 | 0.68 | 0.6393 |
0.9485 | 11.92 | 17000 | 3.0720 | 0.6755 | 0.6420 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for haryoaw/scenario-kd-from-scratch-gold-silver-data-tweet_eval-sentiment-model-xlm-roberta
Base model
FacebookAI/xlm-roberta-base