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20230831142618

Text Classification
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PyTorch
TensorBoard
bert
Generated from Trainer
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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: '20230831142618'
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+ results: []
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+ ---
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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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+
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+ # 20230831142618
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+
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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: 0.6294
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+ - Accuracy: 0.5016
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | No log | 1.0 | 340 | 0.6452 | 0.5 |
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+ | 0.6361 | 2.0 | 680 | 0.6325 | 0.5 |
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+ | 0.6378 | 3.0 | 1020 | 0.6175 | 0.5 |
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+ | 0.6378 | 4.0 | 1360 | 0.6705 | 0.5 |
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+ | 0.6367 | 5.0 | 1700 | 0.6476 | 0.5 |
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+ | 0.6284 | 6.0 | 2040 | 0.6180 | 0.5 |
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+ | 0.6284 | 7.0 | 2380 | 0.6174 | 0.5 |
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+ | 0.6308 | 8.0 | 2720 | 0.6441 | 0.5 |
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+ | 0.622 | 9.0 | 3060 | 0.6199 | 0.5 |
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+ | 0.622 | 10.0 | 3400 | 0.6222 | 0.5 |
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+ | 0.6264 | 11.0 | 3740 | 0.6177 | 0.5 |
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+ | 0.6249 | 12.0 | 4080 | 0.6172 | 0.5 |
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+ | 0.6249 | 13.0 | 4420 | 0.6872 | 0.5 |
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+ | 0.6205 | 14.0 | 4760 | 0.6174 | 0.5 |
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+ | 0.6347 | 15.0 | 5100 | 0.6236 | 0.5 |
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+ | 0.6347 | 16.0 | 5440 | 0.6170 | 0.5 |
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+ | 0.6369 | 17.0 | 5780 | 0.6180 | 0.5 |
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+ | 0.623 | 18.0 | 6120 | 0.6256 | 0.5 |
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+ | 0.623 | 19.0 | 6460 | 0.6349 | 0.5 |
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+ | 0.6278 | 20.0 | 6800 | 0.6554 | 0.5 |
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+ | 0.6255 | 21.0 | 7140 | 0.6173 | 0.5 |
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+ | 0.6255 | 22.0 | 7480 | 0.6215 | 0.5 |
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+ | 0.6286 | 23.0 | 7820 | 0.6201 | 0.5 |
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+ | 0.6235 | 24.0 | 8160 | 0.6176 | 0.5 |
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+ | 0.6289 | 25.0 | 8500 | 0.6216 | 0.5 |
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+ | 0.6289 | 26.0 | 8840 | 0.6522 | 0.5 |
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+ | 0.6236 | 27.0 | 9180 | 0.6193 | 0.5 |
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+ | 0.6227 | 28.0 | 9520 | 0.6175 | 0.5 |
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+ | 0.6227 | 29.0 | 9860 | 0.6504 | 0.5 |
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+ | 0.6211 | 30.0 | 10200 | 0.6442 | 0.5 |
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+ | 0.623 | 31.0 | 10540 | 0.6181 | 0.5 |
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+ | 0.623 | 32.0 | 10880 | 0.6220 | 0.5 |
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+ | 0.6206 | 33.0 | 11220 | 0.6185 | 0.5 |
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+ | 0.621 | 34.0 | 11560 | 0.6238 | 0.5 |
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+ | 0.621 | 35.0 | 11900 | 0.6277 | 0.5 |
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+ | 0.6216 | 36.0 | 12240 | 0.6352 | 0.5 |
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+ | 0.6211 | 37.0 | 12580 | 0.6170 | 0.5 |
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+ | 0.6211 | 38.0 | 12920 | 0.6169 | 0.5 |
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+ | 0.6203 | 39.0 | 13260 | 0.6410 | 0.5 |
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+ | 0.619 | 40.0 | 13600 | 0.6190 | 0.5 |
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+ | 0.619 | 41.0 | 13940 | 0.6228 | 0.5 |
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+ | 0.6214 | 42.0 | 14280 | 0.6214 | 0.5 |
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+ | 0.617 | 43.0 | 14620 | 0.6212 | 0.5 |
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+ | 0.617 | 44.0 | 14960 | 0.6172 | 0.5 |
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+ | 0.6211 | 45.0 | 15300 | 0.6309 | 0.5 |
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+ | 0.6168 | 46.0 | 15640 | 0.6250 | 0.5 |
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+ | 0.6168 | 47.0 | 15980 | 0.6371 | 0.5 |
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+ | 0.621 | 48.0 | 16320 | 0.6187 | 0.5 |
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+ | 0.6179 | 49.0 | 16660 | 0.6272 | 0.5 |
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+ | 0.6185 | 50.0 | 17000 | 0.6184 | 0.5 |
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+ | 0.6185 | 51.0 | 17340 | 0.6207 | 0.5 |
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+ | 0.6154 | 52.0 | 17680 | 0.6187 | 0.5 |
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+ | 0.6204 | 53.0 | 18020 | 0.6225 | 0.5 |
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+ | 0.6204 | 54.0 | 18360 | 0.6177 | 0.5 |
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+ | 0.6161 | 55.0 | 18700 | 0.6319 | 0.5 |
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+ | 0.6231 | 56.0 | 19040 | 0.6109 | 0.5 |
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+ | 0.6231 | 57.0 | 19380 | 0.6058 | 0.5 |
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+ | 0.6051 | 58.0 | 19720 | 0.6064 | 0.5 |
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+ | 0.5939 | 59.0 | 20060 | 0.6035 | 0.5 |
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+ | 0.5939 | 60.0 | 20400 | 0.6428 | 0.5125 |
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+ | 0.5818 | 61.0 | 20740 | 0.5962 | 0.5 |
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+ | 0.5724 | 62.0 | 21080 | 0.5954 | 0.5 |
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+ | 0.5724 | 63.0 | 21420 | 0.5971 | 0.5 |
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+ | 0.565 | 64.0 | 21760 | 0.6361 | 0.5047 |
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+ | 0.563 | 65.0 | 22100 | 0.6182 | 0.5016 |
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+ | 0.563 | 66.0 | 22440 | 0.6006 | 0.5 |
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+ | 0.5456 | 67.0 | 22780 | 0.6329 | 0.5016 |
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+ | 0.5507 | 68.0 | 23120 | 0.6332 | 0.5031 |
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+ | 0.5507 | 69.0 | 23460 | 0.6358 | 0.5 |
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+ | 0.5446 | 70.0 | 23800 | 0.6326 | 0.5031 |
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+ | 0.5364 | 71.0 | 24140 | 0.6283 | 0.5016 |
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+ | 0.5364 | 72.0 | 24480 | 0.6214 | 0.5016 |
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+ | 0.5335 | 73.0 | 24820 | 0.6173 | 0.5 |
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+ | 0.532 | 74.0 | 25160 | 0.6214 | 0.5016 |
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+ | 0.5274 | 75.0 | 25500 | 0.6298 | 0.5016 |
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+ | 0.5274 | 76.0 | 25840 | 0.6313 | 0.5016 |
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+ | 0.5265 | 77.0 | 26180 | 0.6241 | 0.5 |
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+ | 0.5233 | 78.0 | 26520 | 0.6215 | 0.5 |
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+ | 0.5233 | 79.0 | 26860 | 0.6280 | 0.5016 |
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+ | 0.5235 | 80.0 | 27200 | 0.6294 | 0.5016 |
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+
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+
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+ ### Framework versions
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+
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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