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V3_20230929-3-xlm-roberta-base-new
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.5509
- Loss: 2.1676
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Accuracy | Validation Loss |
---|---|---|---|---|
4.4138 | 0.46 | 200 | 0.2723 | nan |
4.0972 | 0.91 | 400 | 0.3135 | nan |
3.7299 | 1.37 | 600 | 0.3289 | nan |
3.7476 | 1.82 | 800 | 0.3242 | 3.6812 |
3.8098 | 2.28 | 1000 | 0.4011 | 3.5966 |
3.6111 | 2.73 | 1200 | 0.4 | 2.8744 |
3.3202 | 3.19 | 1400 | 0.4334 | 2.9269 |
3.3557 | 3.64 | 1600 | 0.3649 | nan |
3.198 | 4.1 | 1800 | 0.4349 | nan |
3.1623 | 4.56 | 2000 | 0.4237 | 2.9731 |
3.1379 | 5.01 | 2200 | 0.4521 | nan |
3.0795 | 5.47 | 2400 | 0.4538 | 2.8971 |
3.0176 | 5.92 | 2600 | 0.4138 | 3.0068 |
2.9956 | 6.38 | 2800 | 0.4729 | nan |
2.9666 | 6.83 | 3000 | 0.4674 | 2.3240 |
2.9124 | 7.29 | 3200 | 0.5039 | nan |
2.9806 | 7.74 | 3400 | 0.4457 | nan |
2.7471 | 8.2 | 3600 | 0.5138 | 2.4373 |
2.7762 | 8.66 | 3800 | 0.4963 | 2.4425 |
2.7485 | 9.11 | 4000 | 0.5302 | nan |
2.6488 | 9.57 | 4200 | 0.5499 | 2.3581 |
2.69 | 10.02 | 4400 | 0.5066 | 2.3862 |
2.6669 | 10.48 | 4600 | 0.4802 | 2.4588 |
2.5595 | 10.93 | 4800 | 0.4938 | 2.4186 |
2.5512 | 11.39 | 5000 | 0.5076 | 2.5922 |
2.5686 | 11.85 | 5200 | 0.5648 | nan |
2.5772 | 12.3 | 5400 | 0.5480 | 2.4634 |
2.5701 | 12.76 | 5600 | 0.5497 | 2.5381 |
2.3937 | 13.21 | 5800 | 0.5310 | nan |
2.5274 | 13.67 | 6000 | 0.5681 | nan |
2.3513 | 14.12 | 6200 | 0.5671 | nan |
2.529 | 14.58 | 6400 | 0.5509 | 2.1676 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3