--- library_name: transformers license: apache-2.0 base_model: albert/albert-xlarge-v2 tags: - generated_from_trainer metrics: - accuracy - rouge model-index: - name: b0ef99bd633b80a07ed4b29b0a2c5d91 results: [] --- # b0ef99bd633b80a07ed4b29b0a2c5d91 This model is a fine-tuned version of [albert/albert-xlarge-v2](https://huggingface.co/albert/albert-xlarge-v2) on the dim/tldr_news dataset. It achieves the following results on the evaluation set: - Loss: 1.4613 - Data Size: 1.0 - Epoch Runtime: 25.1440 - Accuracy: 0.2756 - F1 Macro: 0.0864 - Rouge1: 0.2752 - Rouge2: 0.0 - Rougel: 0.2749 - Rougelsum: 0.2756 ## 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: 8 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 4 - total_train_batch_size: 32 - total_eval_batch_size: 32 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: constant - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro | Rouge1 | Rouge2 | Rougel | Rougelsum | |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|:------:|:------:|:------:|:---------:| | No log | 0 | 0 | 1.7195 | 0 | 2.3979 | 0.2173 | 0.0714 | 0.2166 | 0.0 | 0.2173 | 0.2173 | | No log | 1 | 178 | 1.6290 | 0.0078 | 3.4422 | 0.2472 | 0.0793 | 0.2472 | 0.0 | 0.2472 | 0.2464 | | No log | 2 | 356 | 1.6889 | 0.0156 | 2.8855 | 0.0987 | 0.0825 | 0.0987 | 0.0 | 0.0987 | 0.0987 | | No log | 3 | 534 | 1.4780 | 0.0312 | 3.2746 | 0.2479 | 0.1712 | 0.2479 | 0.0 | 0.2472 | 0.2479 | | No log | 4 | 712 | 1.5387 | 0.0625 | 4.0645 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | No log | 5 | 890 | 1.4859 | 0.125 | 5.4759 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 0.0972 | 6 | 1068 | 1.4760 | 0.25 | 8.3402 | 0.2173 | 0.0714 | 0.2166 | 0.0 | 0.2173 | 0.2173 | | 1.461 | 7 | 1246 | 1.4646 | 0.5 | 13.7672 | 0.2486 | 0.0796 | 0.2486 | 0.0 | 0.2486 | 0.2479 | | 1.4427 | 8.0 | 1424 | 1.4623 | 1.0 | 25.4379 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4515 | 9.0 | 1602 | 1.4538 | 1.0 | 25.2654 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4354 | 10.0 | 1780 | 1.4681 | 1.0 | 25.2701 | 0.2486 | 0.0796 | 0.2486 | 0.0 | 0.2486 | 0.2479 | | 1.4487 | 11.0 | 1958 | 1.4548 | 1.0 | 25.2500 | 0.2401 | 0.0774 | 0.2401 | 0.0 | 0.2408 | 0.2393 | | 1.4558 | 12.0 | 2136 | 1.4588 | 1.0 | 25.2566 | 0.2401 | 0.0774 | 0.2401 | 0.0 | 0.2408 | 0.2393 | | 1.4562 | 13.0 | 2314 | 1.4537 | 1.0 | 25.1478 | 0.2706 | 0.1402 | 0.2699 | 0.0 | 0.2692 | 0.2706 | | 1.4467 | 14.0 | 2492 | 1.4537 | 1.0 | 25.1871 | 0.2173 | 0.0714 | 0.2166 | 0.0 | 0.2173 | 0.2173 | | 1.4535 | 15.0 | 2670 | 1.4568 | 1.0 | 25.1471 | 0.2486 | 0.0796 | 0.2486 | 0.0 | 0.2486 | 0.2479 | | 1.4578 | 16.0 | 2848 | 1.4544 | 1.0 | 25.1672 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4413 | 17.0 | 3026 | 1.4510 | 1.0 | 25.2195 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4454 | 18.0 | 3204 | 1.4521 | 1.0 | 25.1672 | 0.2486 | 0.0796 | 0.2486 | 0.0 | 0.2486 | 0.2479 | | 1.4468 | 19.0 | 3382 | 1.4508 | 1.0 | 25.0699 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4568 | 20.0 | 3560 | 1.4548 | 1.0 | 25.2263 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4404 | 21.0 | 3738 | 1.4542 | 1.0 | 25.2249 | 0.2401 | 0.0774 | 0.2401 | 0.0 | 0.2408 | 0.2393 | | 1.4448 | 22.0 | 3916 | 1.4589 | 1.0 | 25.3352 | 0.2486 | 0.0796 | 0.2486 | 0.0 | 0.2486 | 0.2479 | | 1.4398 | 23.0 | 4094 | 1.4506 | 1.0 | 25.2263 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4484 | 24.0 | 4272 | 1.4517 | 1.0 | 25.2167 | 0.2486 | 0.0796 | 0.2486 | 0.0 | 0.2486 | 0.2479 | | 1.4381 | 25.0 | 4450 | 1.4647 | 1.0 | 25.2744 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4482 | 26.0 | 4628 | 1.4524 | 1.0 | 25.5011 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | | 1.4197 | 27.0 | 4806 | 1.4613 | 1.0 | 25.1440 | 0.2756 | 0.0864 | 0.2752 | 0.0 | 0.2749 | 0.2756 | ### Framework versions - Transformers 4.57.0 - Pytorch 2.8.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.1