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roberta-base-roberta-base-TF-weight0.5-epoch5
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.4274
- Cls loss: 0.5846
- Lm loss: 4.1354
- Cls Accuracy: 0.7533
- Cls F1: 0.7495
- Cls Precision: 0.7581
- Cls Recall: 0.7533
- Perplexity: 62.51
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Cls loss | Lm loss | Cls Accuracy | Cls F1 | Cls Precision | Cls Recall | Perplexity |
---|---|---|---|---|---|---|---|---|---|---|
4.9675 | 1.0 | 3470 | 4.6427 | 0.6907 | 4.2975 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 73.51 |
4.6381 | 2.0 | 6940 | 4.5451 | 0.6935 | 4.1983 | 0.4599 | 0.2898 | 0.2115 | 0.4599 | 66.58 |
4.5086 | 3.0 | 10410 | 4.5036 | 0.6902 | 4.1585 | 0.5401 | 0.3788 | 0.2917 | 0.5401 | 63.98 |
4.4302 | 4.0 | 13880 | 4.4818 | 0.6877 | 4.1379 | 0.5447 | 0.3910 | 0.6764 | 0.5447 | 62.67 |
4.3315 | 5.0 | 17350 | 4.4274 | 0.5846 | 4.1354 | 0.7533 | 0.7495 | 0.7581 | 0.7533 | 62.51 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1