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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: '20230822185221'
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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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+ # 20230822185221
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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: 0.3289
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+ - Accuracy: 0.7329
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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: 0.002
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+ - train_batch_size: 8
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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: 60.0
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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 | 312 | 0.5077 | 0.5307 |
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+ | 0.4439 | 2.0 | 624 | 0.3971 | 0.4874 |
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+ | 0.4439 | 3.0 | 936 | 0.3574 | 0.5379 |
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+ | 0.4231 | 4.0 | 1248 | 0.3625 | 0.5776 |
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+ | 0.4071 | 5.0 | 1560 | 0.4937 | 0.5343 |
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+ | 0.4071 | 6.0 | 1872 | 0.3738 | 0.5668 |
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+ | 0.3956 | 7.0 | 2184 | 0.4081 | 0.4729 |
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+ | 0.3956 | 8.0 | 2496 | 0.3386 | 0.6209 |
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+ | 0.3905 | 9.0 | 2808 | 0.4147 | 0.4729 |
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+ | 0.3888 | 10.0 | 3120 | 0.3353 | 0.6354 |
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+ | 0.3888 | 11.0 | 3432 | 0.3540 | 0.6282 |
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+ | 0.3992 | 12.0 | 3744 | 0.3453 | 0.5848 |
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+ | 0.372 | 13.0 | 4056 | 0.3265 | 0.6895 |
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+ | 0.372 | 14.0 | 4368 | 0.3575 | 0.6426 |
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+ | 0.3643 | 15.0 | 4680 | 0.3304 | 0.6498 |
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+ | 0.3643 | 16.0 | 4992 | 0.3633 | 0.6715 |
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+ | 0.3666 | 17.0 | 5304 | 0.5230 | 0.5343 |
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+ | 0.3517 | 18.0 | 5616 | 0.3384 | 0.6462 |
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+ | 0.3517 | 19.0 | 5928 | 0.3293 | 0.6823 |
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+ | 0.3519 | 20.0 | 6240 | 0.3613 | 0.6823 |
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+ | 0.338 | 21.0 | 6552 | 0.3242 | 0.7256 |
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+ | 0.338 | 22.0 | 6864 | 0.3399 | 0.7184 |
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+ | 0.3316 | 23.0 | 7176 | 0.3392 | 0.7004 |
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+ | 0.3316 | 24.0 | 7488 | 0.3343 | 0.6534 |
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+ | 0.3266 | 25.0 | 7800 | 0.3467 | 0.7112 |
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+ | 0.3213 | 26.0 | 8112 | 0.3419 | 0.7040 |
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+ | 0.3213 | 27.0 | 8424 | 0.3190 | 0.7112 |
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+ | 0.3177 | 28.0 | 8736 | 0.3205 | 0.6931 |
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+ | 0.3187 | 29.0 | 9048 | 0.3303 | 0.7076 |
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+ | 0.3187 | 30.0 | 9360 | 0.3268 | 0.7148 |
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+ | 0.3162 | 31.0 | 9672 | 0.3274 | 0.7148 |
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+ | 0.3162 | 32.0 | 9984 | 0.3311 | 0.7112 |
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+ | 0.3132 | 33.0 | 10296 | 0.3454 | 0.7148 |
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+ | 0.3087 | 34.0 | 10608 | 0.3250 | 0.7076 |
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+ | 0.3087 | 35.0 | 10920 | 0.3266 | 0.7076 |
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+ | 0.3076 | 36.0 | 11232 | 0.3347 | 0.7292 |
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+ | 0.3071 | 37.0 | 11544 | 0.3308 | 0.7112 |
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+ | 0.3071 | 38.0 | 11856 | 0.3272 | 0.7220 |
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+ | 0.3061 | 39.0 | 12168 | 0.3301 | 0.7148 |
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+ | 0.3061 | 40.0 | 12480 | 0.3226 | 0.7256 |
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+ | 0.3006 | 41.0 | 12792 | 0.3285 | 0.7365 |
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+ | 0.3016 | 42.0 | 13104 | 0.3226 | 0.7148 |
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+ | 0.3016 | 43.0 | 13416 | 0.3291 | 0.7220 |
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+ | 0.2984 | 44.0 | 13728 | 0.3377 | 0.7112 |
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+ | 0.2976 | 45.0 | 14040 | 0.3326 | 0.7220 |
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+ | 0.2976 | 46.0 | 14352 | 0.3341 | 0.7292 |
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+ | 0.2967 | 47.0 | 14664 | 0.3187 | 0.7184 |
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+ | 0.2967 | 48.0 | 14976 | 0.3322 | 0.7148 |
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+ | 0.2953 | 49.0 | 15288 | 0.3269 | 0.7365 |
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+ | 0.2911 | 50.0 | 15600 | 0.3256 | 0.7365 |
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+ | 0.2911 | 51.0 | 15912 | 0.3252 | 0.7256 |
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+ | 0.2929 | 52.0 | 16224 | 0.3251 | 0.7292 |
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+ | 0.2904 | 53.0 | 16536 | 0.3258 | 0.7256 |
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+ | 0.2904 | 54.0 | 16848 | 0.3358 | 0.7220 |
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+ | 0.2895 | 55.0 | 17160 | 0.3219 | 0.7329 |
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+ | 0.2895 | 56.0 | 17472 | 0.3322 | 0.7329 |
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+ | 0.2887 | 57.0 | 17784 | 0.3259 | 0.7365 |
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+ | 0.2883 | 58.0 | 18096 | 0.3260 | 0.7292 |
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+ | 0.2883 | 59.0 | 18408 | 0.3276 | 0.7365 |
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+ | 0.2874 | 60.0 | 18720 | 0.3289 | 0.7329 |
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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