wikipedia_13
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9275
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 13
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40000
- training_steps: 100000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.4657 | 2000 | 8.0872 |
| 8.1326 | 2.9315 | 4000 | 7.3975 |
| 8.1326 | 4.3972 | 6000 | 7.2718 |
| 7.2846 | 5.8630 | 8000 | 7.1835 |
| 7.2846 | 7.3287 | 10000 | 7.0992 |
| 7.1078 | 8.7944 | 12000 | 7.0331 |
| 7.1078 | 10.2602 | 14000 | 6.9494 |
| 6.942 | 11.7259 | 16000 | 6.8899 |
| 6.942 | 13.1916 | 18000 | 6.7822 |
| 6.7676 | 14.6574 | 20000 | 6.7185 |
| 6.7676 | 16.1231 | 22000 | 6.6536 |
| 6.5959 | 17.5889 | 24000 | 6.5431 |
| 6.5959 | 19.0546 | 26000 | 6.3925 |
| 6.3624 | 20.5203 | 28000 | 6.2119 |
| 6.3624 | 21.9861 | 30000 | 5.9526 |
| 5.9309 | 23.4518 | 32000 | 5.4162 |
| 5.9309 | 24.9176 | 34000 | 5.0255 |
| 5.0575 | 26.3833 | 36000 | 4.7680 |
| 5.0575 | 27.8490 | 38000 | 4.5020 |
| 4.5282 | 29.3148 | 40000 | 4.3214 |
| 4.5282 | 30.7805 | 42000 | 4.1312 |
| 4.1335 | 32.2462 | 44000 | 3.9708 |
| 4.1335 | 33.7120 | 46000 | 3.8616 |
| 3.8339 | 35.1777 | 48000 | 3.7640 |
| 3.8339 | 36.6435 | 50000 | 3.7074 |
| 3.6042 | 38.1092 | 52000 | 3.6360 |
| 3.6042 | 39.5749 | 54000 | 3.5203 |
| 3.4291 | 41.0407 | 56000 | 3.4424 |
| 3.4291 | 42.5064 | 58000 | 3.4276 |
| 3.286 | 43.9722 | 60000 | 3.3797 |
| 3.286 | 45.4379 | 62000 | 3.3277 |
| 3.1748 | 46.9036 | 64000 | 3.2922 |
| 3.1748 | 48.3694 | 66000 | 3.2361 |
| 3.0842 | 49.8351 | 68000 | 3.2043 |
| 3.0842 | 51.3008 | 70000 | 3.1870 |
| 3.0082 | 52.7666 | 72000 | 3.1487 |
| 3.0082 | 54.2323 | 74000 | 3.1257 |
| 2.9483 | 55.6981 | 76000 | 3.1001 |
| 2.9483 | 57.1638 | 78000 | 3.0694 |
| 2.8885 | 58.6295 | 80000 | 3.0605 |
| 2.8885 | 60.0953 | 82000 | 3.0568 |
| 2.8416 | 61.5610 | 84000 | 3.0083 |
| 2.8416 | 63.0267 | 86000 | 3.0188 |
| 2.8064 | 64.4925 | 88000 | 3.0213 |
| 2.8064 | 65.9582 | 90000 | 2.9645 |
| 2.7717 | 67.4240 | 92000 | 2.9901 |
| 2.7717 | 68.8897 | 94000 | 2.9684 |
| 2.7441 | 70.3554 | 96000 | 2.9565 |
| 2.7441 | 71.8212 | 98000 | 2.9547 |
| 2.7289 | 73.2869 | 100000 | 2.9275 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
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