lora_alpha_64_drop_0.3_rank_32_seed_42_merges_40_08062024
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4618
- Accuracy: 0.8305
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: 0.0003
- 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: 25.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3456 | 1.0 | 12272 | 0.4626 | 0.8289 |
0.3458 | 2.0 | 24544 | 0.4889 | 0.8253 |
0.3402 | 3.0 | 36816 | 0.4702 | 0.8285 |
0.3445 | 4.0 | 49088 | 0.4648 | 0.8333 |
0.3408 | 5.0 | 61360 | 0.4701 | 0.8301 |
0.341 | 6.0 | 73632 | 0.4628 | 0.8309 |
0.3275 | 7.0 | 85904 | 0.4700 | 0.8281 |
0.3455 | 8.0 | 98176 | 0.4572 | 0.8305 |
0.3455 | 9.0 | 110448 | 0.4795 | 0.8321 |
0.3336 | 10.0 | 122720 | 0.4597 | 0.8273 |
0.3317 | 11.0 | 134992 | 0.4716 | 0.8309 |
0.33 | 12.0 | 147264 | 0.4605 | 0.8341 |
0.3279 | 13.0 | 159536 | 0.4824 | 0.8265 |
0.323 | 14.0 | 171808 | 0.4634 | 0.8285 |
0.3276 | 15.0 | 184080 | 0.4876 | 0.8305 |
0.3254 | 16.0 | 196352 | 0.4658 | 0.8297 |
0.3349 | 17.0 | 208624 | 0.4713 | 0.8297 |
0.334 | 18.0 | 220896 | 0.4759 | 0.8285 |
0.3319 | 19.0 | 233168 | 0.4664 | 0.8321 |
0.3425 | 20.0 | 245440 | 0.4761 | 0.8285 |
0.3366 | 21.0 | 257712 | 0.4599 | 0.8329 |
0.3475 | 22.0 | 269984 | 0.4614 | 0.8313 |
0.3416 | 23.0 | 282256 | 0.4590 | 0.8317 |
0.3455 | 24.0 | 294528 | 0.4630 | 0.8305 |
0.3399 | 25.0 | 306800 | 0.4618 | 0.8305 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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