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Greg-Sentiment-classifier

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bert
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update model card README.md

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@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0161
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- - F1: 0.3222
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  ## Model description
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@@ -36,30 +36,80 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0005
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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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: 12
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.9805 | 1.0 | 499 | 1.0211 | 0.2347 |
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- | 1.0289 | 2.0 | 998 | 1.0175 | 0.2347 |
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- | 0.9924 | 3.0 | 1497 | 1.0189 | 0.2347 |
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- | 1.0319 | 4.0 | 1996 | 1.0165 | 0.3222 |
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- | 1.0351 | 5.0 | 2495 | 1.0179 | 0.3222 |
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- | 1.0339 | 6.0 | 2994 | 1.0172 | 0.3222 |
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- | 1.0039 | 7.0 | 3493 | 1.0163 | 0.3222 |
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- | 1.0299 | 8.0 | 3992 | 1.0164 | 0.3222 |
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- | 0.9914 | 9.0 | 4491 | 1.0168 | 0.3222 |
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- | 1.0038 | 10.0 | 4990 | 1.0162 | 0.3222 |
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- | 1.0399 | 11.0 | 5489 | 1.0161 | 0.3222 |
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- | 0.996 | 12.0 | 5988 | 1.0161 | 0.3222 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7903
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+ - F1: 0.7123
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.6542 | 0.03 | 16 | 0.8127 | 0.6943 |
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+ | 0.574 | 0.06 | 32 | 0.7935 | 0.6969 |
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+ | 0.7078 | 0.1 | 48 | 0.8009 | 0.6957 |
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+ | 0.5408 | 0.13 | 64 | 0.7863 | 0.7014 |
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+ | 0.5343 | 0.16 | 80 | 0.8077 | 0.6996 |
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+ | 0.5768 | 0.19 | 96 | 0.8239 | 0.6900 |
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+ | 0.6633 | 0.22 | 112 | 0.7942 | 0.7028 |
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+ | 0.5409 | 0.26 | 128 | 0.8025 | 0.6960 |
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+ | 0.7043 | 0.29 | 144 | 0.7954 | 0.6813 |
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+ | 0.5358 | 0.32 | 160 | 0.8058 | 0.6988 |
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+ | 0.5558 | 0.35 | 176 | 0.8476 | 0.6799 |
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+ | 0.5759 | 0.38 | 192 | 0.8232 | 0.7017 |
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+ | 0.596 | 0.42 | 208 | 0.8240 | 0.7072 |
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+ | 0.5977 | 0.45 | 224 | 0.8683 | 0.6947 |
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+ | 0.5655 | 0.48 | 240 | 0.8378 | 0.7053 |
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+ | 0.6274 | 0.51 | 256 | 0.8175 | 0.6980 |
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+ | 0.4952 | 0.55 | 272 | 0.8203 | 0.6957 |
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+ | 0.6501 | 0.58 | 288 | 0.8236 | 0.7014 |
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+ | 0.5365 | 0.61 | 304 | 0.8082 | 0.7059 |
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+ | 0.5598 | 0.64 | 320 | 0.8052 | 0.7121 |
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+ | 0.5692 | 0.67 | 336 | 0.7989 | 0.7075 |
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+ | 0.526 | 0.71 | 352 | 0.8030 | 0.6961 |
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+ | 0.5505 | 0.74 | 368 | 0.8157 | 0.7137 |
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+ | 0.4759 | 0.77 | 384 | 0.8466 | 0.6937 |
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+ | 0.6622 | 0.8 | 400 | 0.8518 | 0.6982 |
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+ | 0.6298 | 0.83 | 416 | 0.8272 | 0.6976 |
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+ | 0.6311 | 0.87 | 432 | 0.8445 | 0.6793 |
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+ | 0.5678 | 0.9 | 448 | 0.8096 | 0.6897 |
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+ | 0.6687 | 0.93 | 464 | 0.7948 | 0.6968 |
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+ | 0.6654 | 0.96 | 480 | 0.8047 | 0.7076 |
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+ | 0.6572 | 0.99 | 496 | 0.7944 | 0.7037 |
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+ | 0.5845 | 1.03 | 512 | 0.7772 | 0.7030 |
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+ | 0.6611 | 1.06 | 528 | 0.7829 | 0.7005 |
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+ | 0.4988 | 1.09 | 544 | 0.7953 | 0.7070 |
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+ | 0.6355 | 1.12 | 560 | 0.8252 | 0.6983 |
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+ | 0.5464 | 1.15 | 576 | 0.8293 | 0.7044 |
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+ | 0.6188 | 1.19 | 592 | 0.8077 | 0.7073 |
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+ | 0.5125 | 1.22 | 608 | 0.7975 | 0.7041 |
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+ | 0.6221 | 1.25 | 624 | 0.7947 | 0.7041 |
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+ | 0.5806 | 1.28 | 640 | 0.8027 | 0.6983 |
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+ | 0.6335 | 1.31 | 656 | 0.7992 | 0.7027 |
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+ | 0.6283 | 1.35 | 672 | 0.7836 | 0.7055 |
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+ | 0.6485 | 1.38 | 688 | 0.7891 | 0.7104 |
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+ | 0.5596 | 1.41 | 704 | 0.8146 | 0.7015 |
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+ | 0.4928 | 1.44 | 720 | 0.7998 | 0.7088 |
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+ | 0.5809 | 1.47 | 736 | 0.7850 | 0.7056 |
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+ | 0.5117 | 1.51 | 752 | 0.7994 | 0.7053 |
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+ | 0.6012 | 1.54 | 768 | 0.7960 | 0.7081 |
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+ | 0.5213 | 1.57 | 784 | 0.8109 | 0.7034 |
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+ | 0.6018 | 1.6 | 800 | 0.7927 | 0.7134 |
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+ | 0.5851 | 1.64 | 816 | 0.7978 | 0.7108 |
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+ | 0.6571 | 1.67 | 832 | 0.8131 | 0.7004 |
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+ | 0.5215 | 1.7 | 848 | 0.7942 | 0.7146 |
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+ | 0.5372 | 1.73 | 864 | 0.7957 | 0.7110 |
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+ | 0.5511 | 1.76 | 880 | 0.7915 | 0.7138 |
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+ | 0.5991 | 1.8 | 896 | 0.7899 | 0.7121 |
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+ | 0.6128 | 1.83 | 912 | 0.7879 | 0.7136 |
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+ | 0.5493 | 1.86 | 928 | 0.7960 | 0.7099 |
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+ | 0.6304 | 1.89 | 944 | 0.7924 | 0.7102 |
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+ | 0.4456 | 1.92 | 960 | 0.7904 | 0.7126 |
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+ | 0.5484 | 1.96 | 976 | 0.7906 | 0.7127 |
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+ | 0.515 | 1.99 | 992 | 0.7903 | 0.7123 |
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  ### Framework versions