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roberta
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5264
- Ndcg: 0.4471
- Accuracy: 0.2959
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Ndcg | Accuracy |
|---|---|---|---|---|---|
| 1.5844 | 0.07 | 413 | 1.5508 | 0.4255 | 0.2786 |
| 1.5709 | 0.13 | 826 | 1.5537 | 0.4204 | 0.2854 |
| 1.5581 | 0.2 | 1239 | 1.5557 | 0.4252 | 0.2777 |
| 1.5723 | 0.27 | 1652 | 1.5498 | 0.4329 | 0.2833 |
| 1.5543 | 0.33 | 2065 | 1.5430 | 0.4272 | 0.2872 |
| 1.549 | 0.4 | 2478 | 1.5391 | 0.4371 | 0.2899 |
| 1.5527 | 0.47 | 2891 | 1.5420 | 0.4328 | 0.2838 |
| 1.5583 | 0.53 | 3304 | 1.5430 | 0.4371 | 0.2882 |
| 1.537 | 0.6 | 3717 | 1.5371 | 0.4395 | 0.2904 |
| 1.5381 | 0.67 | 4130 | 1.5410 | 0.4391 | 0.2897 |
| 1.5876 | 0.73 | 4543 | 1.7871 | 0.3264 | 0.2005 |
| 1.5573 | 0.8 | 4956 | 1.5430 | 0.4400 | 0.2917 |
| 1.5577 | 0.87 | 5369 | 1.5576 | 0.4319 | 0.2830 |
| 1.5398 | 0.93 | 5782 | 1.5557 | 0.4140 | 0.2657 |
| 1.5414 | 1.0 | 6195 | 1.5986 | 0.4037 | 0.2617 |
| 1.5439 | 1.07 | 6608 | 1.5459 | 0.4303 | 0.2834 |
| 1.5344 | 1.13 | 7021 | 1.5439 | 0.4325 | 0.2838 |
| 1.544 | 1.2 | 7434 | 1.5498 | 0.4335 | 0.2861 |
| 1.5414 | 1.27 | 7847 | 1.5342 | 0.4422 | 0.2910 |
| 1.5358 | 1.33 | 8260 | 1.5312 | 0.4428 | 0.2940 |
| 1.5347 | 1.4 | 8673 | 1.5303 | 0.4457 | 0.2955 |
| 1.5305 | 1.47 | 9086 | 1.5283 | 0.4454 | 0.2944 |
| 1.5406 | 1.53 | 9499 | 1.5283 | 0.4462 | 0.2952 |
| 1.5316 | 1.6 | 9912 | 1.5283 | 0.4445 | 0.2949 |
| 1.5252 | 1.67 | 10325 | 1.5283 | 0.4465 | 0.2958 |
| 1.5202 | 1.73 | 10738 | 1.5264 | 0.4469 | 0.2949 |
| 1.5313 | 1.8 | 11151 | 1.5273 | 0.4469 | 0.2959 |
| 1.5279 | 1.87 | 11564 | 1.5264 | 0.4470 | 0.2963 |
| 1.5317 | 1.93 | 11977 | 1.5264 | 0.4474 | 0.2964 |
| 1.5208 | 2.0 | 12390 | 1.5264 | 0.4471 | 0.2959 |
Framework versions
- Transformers 4.29.1
- Pytorch 2.0.0-rc1
- Datasets 2.12.0
- Tokenizers 0.13.3
