metadata
tags:
- generated_from_trainer
model-index:
- name: baseline
results: []
baseline
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8173
- Exact Match: 0.024
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: 0.001
- train_batch_size: 100
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 400
- optimizer: Adam with betas=(0.98,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 4000
- num_epochs: 100
- label_smoothing_factor: 0.1
Training results
| Training Loss | Epoch | Step | Validation Loss | Exact Match |
|---|---|---|---|---|
| 6.2658 | 1.0 | 25 | 5.8355 | 0.0 |
| 5.8196 | 2.0 | 50 | 4.9580 | 0.0 |
| 5.1965 | 3.0 | 75 | 4.4378 | 0.0 |
| 4.7235 | 4.0 | 100 | 4.0961 | 0.0 |
| 4.4214 | 5.0 | 125 | 3.9076 | 0.0 |
| 4.2363 | 6.0 | 150 | 3.7785 | 0.0 |
| 4.1005 | 7.0 | 175 | 3.6651 | 0.0 |
| 3.9843 | 8.0 | 200 | 3.5463 | 0.0 |
| 3.8646 | 9.0 | 225 | 3.4428 | 0.0 |
| 3.741 | 10.0 | 250 | 3.3358 | 0.0 |
| 3.6147 | 11.0 | 275 | 3.2427 | 0.0 |
| 3.495 | 12.0 | 300 | 3.1311 | 0.0 |
| 3.3903 | 13.0 | 325 | 3.0348 | 0.0 |
| 3.2919 | 14.0 | 350 | 2.9669 | 0.0 |
| 3.2062 | 15.0 | 375 | 2.9071 | 0.0 |
| 3.137 | 16.0 | 400 | 2.8355 | 0.0 |
| 3.0572 | 17.0 | 425 | 2.7804 | 0.0 |
| 2.9925 | 18.0 | 450 | 2.7326 | 0.0 |
| 2.9289 | 19.0 | 475 | 2.6681 | 0.0 |
| 2.8768 | 20.0 | 500 | 2.6168 | 0.0 |
| 2.8239 | 21.0 | 525 | 2.5649 | 0.0 |
| 2.7689 | 22.0 | 550 | 2.5171 | 0.0 |
| 2.7125 | 23.0 | 575 | 2.4704 | 0.0 |
| 2.6607 | 24.0 | 600 | 2.4268 | 0.0 |
| 2.6149 | 25.0 | 625 | 2.4030 | 0.0 |
| 2.56 | 26.0 | 650 | 2.3599 | 0.001 |
| 2.5085 | 27.0 | 675 | 2.3096 | 0.006 |
| 2.4572 | 28.0 | 700 | 2.2606 | 0.008 |
| 2.4133 | 29.0 | 725 | 2.2313 | 0.009 |
| 2.3613 | 30.0 | 750 | 2.2011 | 0.011 |
| 2.3141 | 31.0 | 775 | 2.1757 | 0.011 |
| 2.2714 | 32.0 | 800 | 2.1362 | 0.013 |
| 2.2226 | 33.0 | 825 | 2.1176 | 0.019 |
| 2.1821 | 34.0 | 850 | 2.0885 | 0.022 |
| 2.1445 | 35.0 | 875 | 2.0810 | 0.022 |
| 2.1082 | 36.0 | 900 | 2.0501 | 0.034 |
| 2.0683 | 37.0 | 925 | 2.0571 | 0.029 |
| 2.0365 | 38.0 | 950 | 2.0318 | 0.028 |
| 2.0003 | 39.0 | 975 | 2.0227 | 0.033 |
| 1.9654 | 40.0 | 1000 | 2.0141 | 0.042 |
| 1.9358 | 41.0 | 1025 | 2.0042 | 0.045 |
| 1.905 | 42.0 | 1050 | 1.9903 | 0.055 |
| 1.878 | 43.0 | 1075 | 2.0076 | 0.057 |
| 1.8517 | 44.0 | 1100 | 1.9761 | 0.057 |
| 1.8233 | 45.0 | 1125 | 1.9952 | 0.063 |
| 1.7934 | 46.0 | 1150 | 1.9562 | 0.062 |
| 1.7636 | 47.0 | 1175 | 1.9776 | 0.068 |
| 1.7445 | 48.0 | 1200 | 1.9503 | 0.066 |
| 1.7226 | 49.0 | 1225 | 1.9616 | 0.065 |
| 1.7013 | 50.0 | 1250 | 1.9516 | 0.067 |
| 1.68 | 51.0 | 1275 | 1.9408 | 0.065 |
| 1.6557 | 52.0 | 1300 | 1.9493 | 0.073 |
| 1.6396 | 53.0 | 1325 | 1.9012 | 0.099 |
| 1.6183 | 54.0 | 1350 | 1.9144 | 0.083 |
| 1.5918 | 55.0 | 1375 | 1.9150 | 0.085 |
| 1.5788 | 56.0 | 1400 | 1.9278 | 0.098 |
| 1.5601 | 57.0 | 1425 | 1.9072 | 0.088 |
| 1.5464 | 58.0 | 1450 | 1.8896 | 0.084 |
| 1.5333 | 59.0 | 1475 | 1.9001 | 0.111 |
| 1.5153 | 60.0 | 1500 | 1.8746 | 0.089 |
| 1.5034 | 61.0 | 1525 | 1.8869 | 0.089 |
| 1.4876 | 62.0 | 1550 | 1.8744 | 0.105 |
| 1.4779 | 63.0 | 1575 | 1.8866 | 0.089 |
| 1.459 | 64.0 | 1600 | 1.8615 | 0.128 |
| 1.4447 | 65.0 | 1625 | 1.8565 | 0.111 |
| 1.4321 | 66.0 | 1650 | 1.8659 | 0.129 |
| 1.4175 | 67.0 | 1675 | 1.8571 | 0.121 |
| 1.4071 | 68.0 | 1700 | 1.8831 | 0.076 |
| 1.3987 | 69.0 | 1725 | 1.8492 | 0.077 |
| 1.3837 | 70.0 | 1750 | 1.8430 | 0.101 |
| 1.374 | 71.0 | 1775 | 1.8455 | 0.082 |
| 1.3645 | 72.0 | 1800 | 1.8506 | 0.064 |
| 1.3537 | 73.0 | 1825 | 1.8345 | 0.07 |
| 1.3441 | 74.0 | 1850 | 1.8267 | 0.115 |
| 1.3348 | 75.0 | 1875 | 1.8504 | 0.084 |
| 1.3205 | 76.0 | 1900 | 1.8470 | 0.08 |
| 1.3108 | 77.0 | 1925 | 1.8397 | 0.089 |
| 1.3028 | 78.0 | 1950 | 1.8657 | 0.073 |
| 1.2978 | 79.0 | 1975 | 1.8595 | 0.067 |
| 1.2875 | 80.0 | 2000 | 1.8322 | 0.073 |
| 1.2753 | 81.0 | 2025 | 1.8697 | 0.04 |
| 1.2707 | 82.0 | 2050 | 1.8426 | 0.085 |
| 1.262 | 83.0 | 2075 | 1.8229 | 0.093 |
| 1.2532 | 84.0 | 2100 | 1.8420 | 0.054 |
| 1.2488 | 85.0 | 2125 | 1.8465 | 0.057 |
| 1.2373 | 86.0 | 2150 | 1.8701 | 0.051 |
| 1.229 | 87.0 | 2175 | 1.8474 | 0.054 |
| 1.2242 | 88.0 | 2200 | 1.8287 | 0.072 |
| 1.2195 | 89.0 | 2225 | 1.8424 | 0.057 |
| 1.212 | 90.0 | 2250 | 1.8663 | 0.062 |
| 1.2033 | 91.0 | 2275 | 1.8447 | 0.044 |
| 1.1994 | 92.0 | 2300 | 1.8287 | 0.058 |
| 1.1907 | 93.0 | 2325 | 1.8425 | 0.05 |
| 1.1847 | 94.0 | 2350 | 1.8993 | 0.004 |
| 1.1805 | 95.0 | 2375 | 1.9007 | 0.014 |
| 1.1739 | 96.0 | 2400 | 1.8792 | 0.015 |
| 1.1697 | 97.0 | 2425 | 1.8315 | 0.02 |
| 1.162 | 98.0 | 2450 | 1.8024 | 0.043 |
| 1.1585 | 99.0 | 2475 | 1.8437 | 0.017 |
| 1.1505 | 100.0 | 2500 | 1.8173 | 0.024 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0