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tiny-mlm-glue-qnli-custom-tokenizer
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 6.2339
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: 3e-05
- 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: constant
- num_epochs: 200
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 7.9951 | 0.4 | 500 | 7.3315 |
| 7.1282 | 0.8 | 1000 | 7.2457 |
| 7.0402 | 1.2 | 1500 | 7.2104 |
| 6.9634 | 1.6 | 2000 | 7.1415 |
| 6.9383 | 2.0 | 2500 | 7.0838 |
| 6.8365 | 2.4 | 3000 | 7.0031 |
| 6.7812 | 2.8 | 3500 | 6.9679 |
| 6.6959 | 3.2 | 4000 | 6.9121 |
| 6.6423 | 3.6 | 4500 | 6.8421 |
| 6.5766 | 4.0 | 5000 | 6.8474 |
| 6.5676 | 4.4 | 5500 | 6.8089 |
| 6.4728 | 4.8 | 6000 | 6.7246 |
| 6.5008 | 5.2 | 6500 | 6.7049 |
| 6.4367 | 5.6 | 7000 | 6.6539 |
| 6.4016 | 6.0 | 7500 | 6.6268 |
| 6.4063 | 6.4 | 8000 | 6.6038 |
| 6.3836 | 6.8 | 8500 | 6.5452 |
| 6.3576 | 7.2 | 9000 | 6.5932 |
| 6.2768 | 7.6 | 9500 | 6.5443 |
| 6.3002 | 8.0 | 10000 | 6.5018 |
| 6.304 | 8.4 | 10500 | 6.5263 |
| 6.2123 | 8.8 | 11000 | 6.4739 |
| 6.2015 | 9.2 | 11500 | 6.4407 |
| 6.1809 | 9.6 | 12000 | 6.4371 |
| 6.1624 | 10.0 | 12500 | 6.4379 |
| 6.1831 | 10.4 | 13000 | 6.3897 |
| 6.163 | 10.8 | 13500 | 6.4086 |
| 6.0881 | 11.2 | 14000 | 6.3902 |
| 6.0474 | 11.6 | 14500 | 6.3229 |
| 6.0454 | 12.0 | 15000 | 6.2995 |
| 6.0491 | 12.4 | 15500 | 6.3559 |
| 6.0045 | 12.8 | 16000 | 6.2820 |
| 6.043 | 13.2 | 16500 | 6.3260 |
| 5.9485 | 13.6 | 17000 | 6.2554 |
| 5.9513 | 14.0 | 17500 | 6.2668 |
| 5.9501 | 14.4 | 18000 | 6.2396 |
| 5.9882 | 14.8 | 18500 | 6.2655 |
| 5.9311 | 15.2 | 19000 | 6.1839 |
| 5.9662 | 15.6 | 19500 | 6.1942 |
| 5.9328 | 16.0 | 20000 | 6.2425 |
| 5.8984 | 16.4 | 20500 | 6.2339 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2
