--- license: mit base_model: facebook/xlm-v-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: scenario-TCR-XLMV-XCOPA-5_data-xcopa_all results: [] --- # scenario-TCR-XLMV-XCOPA-5_data-xcopa_all This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6931 - Accuracy: 0.5125 - F1: 0.4891 ## 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: 214 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 500 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 0.38 | 5 | 0.6925 | 0.5333 | 0.5246 | | No log | 0.77 | 10 | 0.6931 | 0.4867 | 0.4680 | | No log | 1.15 | 15 | 0.6932 | 0.475 | 0.4483 | | No log | 1.54 | 20 | 0.6932 | 0.4658 | 0.4241 | | No log | 1.92 | 25 | 0.6932 | 0.4975 | 0.4724 | | No log | 2.31 | 30 | 0.6931 | 0.5175 | 0.4970 | | No log | 2.69 | 35 | 0.6931 | 0.5142 | 0.4987 | | No log | 3.08 | 40 | 0.6931 | 0.5167 | 0.5026 | | No log | 3.46 | 45 | 0.6931 | 0.53 | 0.5146 | | No log | 3.85 | 50 | 0.6931 | 0.5492 | 0.5292 | | No log | 4.23 | 55 | 0.6931 | 0.5517 | 0.5394 | | No log | 4.62 | 60 | 0.6931 | 0.5508 | 0.5357 | | No log | 5.0 | 65 | 0.6931 | 0.5533 | 0.5387 | | No log | 5.38 | 70 | 0.6930 | 0.5592 | 0.5428 | | No log | 5.77 | 75 | 0.6930 | 0.5608 | 0.5453 | | No log | 6.15 | 80 | 0.6931 | 0.54 | 0.5258 | | No log | 6.54 | 85 | 0.6933 | 0.4958 | 0.4860 | | No log | 6.92 | 90 | 0.6931 | 0.5308 | 0.4987 | | No log | 7.31 | 95 | 0.6931 | 0.53 | 0.5130 | | No log | 7.69 | 100 | 0.6931 | 0.5292 | 0.5074 | | No log | 8.08 | 105 | 0.6931 | 0.5358 | 0.5101 | | No log | 8.46 | 110 | 0.6931 | 0.5225 | 0.4943 | | No log | 8.85 | 115 | 0.6925 | 0.5575 | 0.5354 | | No log | 9.23 | 120 | 0.6931 | 0.5417 | 0.5250 | | No log | 9.62 | 125 | 0.6931 | 0.5133 | 0.4804 | | No log | 10.0 | 130 | 0.6931 | 0.5358 | 0.5004 | | No log | 10.38 | 135 | 0.6931 | 0.5425 | 0.5163 | | No log | 10.77 | 140 | 0.6931 | 0.5433 | 0.5142 | | No log | 11.15 | 145 | 0.6931 | 0.5425 | 0.5103 | | No log | 11.54 | 150 | 0.6931 | 0.5467 | 0.5099 | | No log | 11.92 | 155 | 0.6931 | 0.5358 | 0.4986 | | No log | 12.31 | 160 | 0.6931 | 0.5275 | 0.4841 | | No log | 12.69 | 165 | 0.6931 | 0.5192 | 0.4825 | | No log | 13.08 | 170 | 0.6931 | 0.5283 | 0.4910 | | No log | 13.46 | 175 | 0.6930 | 0.5508 | 0.5131 | | No log | 13.85 | 180 | 0.6930 | 0.5542 | 0.5303 | | No log | 14.23 | 185 | 0.6932 | 0.4908 | 0.4664 | | No log | 14.62 | 190 | 0.6931 | 0.5075 | 0.4802 | | No log | 15.0 | 195 | 0.6932 | 0.5083 | 0.4806 | | No log | 15.38 | 200 | 0.6932 | 0.4625 | 0.4377 | | No log | 15.77 | 205 | 0.6932 | 0.48 | 0.4694 | | No log | 16.15 | 210 | 0.6932 | 0.49 | 0.4742 | | No log | 16.54 | 215 | 0.6931 | 0.5333 | 0.5130 | | No log | 16.92 | 220 | 0.6931 | 0.5217 | 0.4884 | | No log | 17.31 | 225 | 0.6931 | 0.5125 | 0.4891 | ### Framework versions - Transformers 4.33.3 - Pytorch 2.1.1+cu121 - Datasets 2.14.5 - Tokenizers 0.13.3