scenario-TCR_data-cl-massive_all_1_1
This model is a fine-tuned version of facebook/xlm-v-base on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 1.2577
- Accuracy: 0.7991
- F1: 0.7541
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
0.585 | 0.56 | 5000 | 0.9018 | 0.7809 | 0.7207 |
0.344 | 1.11 | 10000 | 0.9305 | 0.7891 | 0.7376 |
0.2938 | 1.67 | 15000 | 0.9186 | 0.7905 | 0.7357 |
0.1892 | 2.22 | 20000 | 1.0155 | 0.7918 | 0.7414 |
0.1781 | 2.78 | 25000 | 1.0659 | 0.7916 | 0.7479 |
0.1064 | 3.33 | 30000 | 1.1471 | 0.7987 | 0.7540 |
0.1014 | 3.89 | 35000 | 1.1831 | 0.7983 | 0.7497 |
0.0731 | 4.45 | 40000 | 1.2577 | 0.7991 | 0.7541 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3
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Base model
facebook/xlm-v-baseEvaluation results
- Accuracy on massivevalidation set self-reported0.799
- F1 on massivevalidation set self-reported0.754