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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- super_glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: '20230831190406' |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# 20230831190406 |
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This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the super_glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6234 |
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- Accuracy: 0.5 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0007 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 11 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 80.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| No log | 1.0 | 340 | 0.6536 | 0.5 | |
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| 0.6466 | 2.0 | 680 | 0.6207 | 0.5 | |
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| 0.6506 | 3.0 | 1020 | 0.6654 | 0.5 | |
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| 0.6506 | 4.0 | 1360 | 0.6698 | 0.5 | |
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| 0.6458 | 5.0 | 1700 | 0.6234 | 0.5 | |
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| 0.6363 | 6.0 | 2040 | 0.6246 | 0.5 | |
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| 0.6363 | 7.0 | 2380 | 0.6367 | 0.5 | |
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| 0.6401 | 8.0 | 2720 | 0.6582 | 0.5 | |
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| 0.6347 | 9.0 | 3060 | 0.6257 | 0.5 | |
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| 0.6347 | 10.0 | 3400 | 0.6281 | 0.5 | |
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| 0.6378 | 11.0 | 3740 | 0.6234 | 0.5 | |
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| 0.637 | 12.0 | 4080 | 0.6274 | 0.5 | |
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| 0.637 | 13.0 | 4420 | 0.6362 | 0.5 | |
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| 0.6313 | 14.0 | 4760 | 0.6290 | 0.5 | |
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| 0.6359 | 15.0 | 5100 | 0.6302 | 0.5 | |
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| 0.6359 | 16.0 | 5440 | 0.6246 | 0.5 | |
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| 0.639 | 17.0 | 5780 | 0.6319 | 0.5 | |
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| 0.6302 | 18.0 | 6120 | 0.6255 | 0.5 | |
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| 0.6302 | 19.0 | 6460 | 0.6325 | 0.5 | |
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| 0.6329 | 20.0 | 6800 | 0.6434 | 0.5 | |
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| 0.6309 | 21.0 | 7140 | 0.6238 | 0.5 | |
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| 0.6309 | 22.0 | 7480 | 0.6237 | 0.5 | |
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| 0.6325 | 23.0 | 7820 | 0.6296 | 0.5 | |
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| 0.6303 | 24.0 | 8160 | 0.6249 | 0.5 | |
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| 0.6357 | 25.0 | 8500 | 0.6235 | 0.5 | |
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| 0.6357 | 26.0 | 8840 | 0.6258 | 0.5 | |
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| 0.6327 | 27.0 | 9180 | 0.6442 | 0.5 | |
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| 0.6309 | 28.0 | 9520 | 0.6329 | 0.5 | |
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| 0.6309 | 29.0 | 9860 | 0.6374 | 0.5 | |
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| 0.6304 | 30.0 | 10200 | 0.6243 | 0.5 | |
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| 0.6311 | 31.0 | 10540 | 0.6302 | 0.5 | |
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| 0.6311 | 32.0 | 10880 | 0.6247 | 0.5 | |
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| 0.6294 | 33.0 | 11220 | 0.6233 | 0.5 | |
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| 0.6303 | 34.0 | 11560 | 0.6252 | 0.5 | |
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| 0.6303 | 35.0 | 11900 | 0.6365 | 0.5 | |
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| 0.63 | 36.0 | 12240 | 0.6300 | 0.5 | |
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| 0.6304 | 37.0 | 12580 | 0.6290 | 0.5 | |
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| 0.6304 | 38.0 | 12920 | 0.6243 | 0.5 | |
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| 0.6288 | 39.0 | 13260 | 0.6440 | 0.5 | |
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| 0.6298 | 40.0 | 13600 | 0.6260 | 0.5 | |
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| 0.6298 | 41.0 | 13940 | 0.6296 | 0.5 | |
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| 0.6292 | 42.0 | 14280 | 0.6245 | 0.5 | |
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| 0.6255 | 43.0 | 14620 | 0.6253 | 0.5 | |
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| 0.6255 | 44.0 | 14960 | 0.6459 | 0.5 | |
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| 0.631 | 45.0 | 15300 | 0.6321 | 0.5 | |
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| 0.6248 | 46.0 | 15640 | 0.6314 | 0.5 | |
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| 0.6248 | 47.0 | 15980 | 0.6335 | 0.5 | |
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| 0.6293 | 48.0 | 16320 | 0.6240 | 0.5 | |
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| 0.6285 | 49.0 | 16660 | 0.6238 | 0.5 | |
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| 0.6277 | 50.0 | 17000 | 0.6247 | 0.5 | |
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| 0.6277 | 51.0 | 17340 | 0.6378 | 0.5 | |
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| 0.625 | 52.0 | 17680 | 0.6237 | 0.5 | |
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| 0.6301 | 53.0 | 18020 | 0.6246 | 0.5 | |
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| 0.6301 | 54.0 | 18360 | 0.6236 | 0.5 | |
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| 0.6247 | 55.0 | 18700 | 0.6237 | 0.5 | |
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| 0.6253 | 56.0 | 19040 | 0.6252 | 0.5 | |
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| 0.6253 | 57.0 | 19380 | 0.6261 | 0.5 | |
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| 0.6243 | 58.0 | 19720 | 0.6250 | 0.5 | |
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| 0.6268 | 59.0 | 20060 | 0.6387 | 0.5 | |
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| 0.6268 | 60.0 | 20400 | 0.6233 | 0.5 | |
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| 0.625 | 61.0 | 20740 | 0.6239 | 0.5 | |
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| 0.6245 | 62.0 | 21080 | 0.6233 | 0.5 | |
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| 0.6245 | 63.0 | 21420 | 0.6256 | 0.5 | |
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| 0.6232 | 64.0 | 21760 | 0.6263 | 0.5 | |
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| 0.6279 | 65.0 | 22100 | 0.6233 | 0.5 | |
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| 0.6279 | 66.0 | 22440 | 0.6339 | 0.5 | |
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| 0.6185 | 67.0 | 22780 | 0.6237 | 0.5 | |
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| 0.627 | 68.0 | 23120 | 0.6246 | 0.5 | |
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| 0.627 | 69.0 | 23460 | 0.6241 | 0.5 | |
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| 0.6242 | 70.0 | 23800 | 0.6254 | 0.5 | |
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| 0.6229 | 71.0 | 24140 | 0.6236 | 0.5 | |
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| 0.6229 | 72.0 | 24480 | 0.6242 | 0.5 | |
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| 0.621 | 73.0 | 24820 | 0.6238 | 0.5 | |
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| 0.6226 | 74.0 | 25160 | 0.6237 | 0.5 | |
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| 0.6222 | 75.0 | 25500 | 0.6233 | 0.5 | |
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| 0.6222 | 76.0 | 25840 | 0.6244 | 0.5 | |
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| 0.6224 | 77.0 | 26180 | 0.6234 | 0.5 | |
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| 0.6212 | 78.0 | 26520 | 0.6239 | 0.5 | |
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| 0.6212 | 79.0 | 26860 | 0.6238 | 0.5 | |
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| 0.6222 | 80.0 | 27200 | 0.6234 | 0.5 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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