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bert_with_absa
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End of training

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  1. README.md +19 -18
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1269
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- - Accuracy: 0.31
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- - F1 Macro: 0.2887
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- - Precision Macro: 0.3551
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- - Recall Macro: 0.3335
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- - Total Tf: [31, 69, 131, 69]
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  ## Model description
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@@ -46,22 +46,23 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - lr_scheduler_warmup_steps: 1
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  - num_epochs: 25
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Total Tf |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:-----------------:|
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- | 1.119 | 1.0 | 2 | 1.0855 | 0.42 | 0.1972 | 0.1400 | 0.3333 | [42, 58, 142, 58] |
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- | 1.1094 | 2.0 | 4 | 1.0932 | 0.35 | 0.2854 | 0.5635 | 0.3243 | [35, 65, 135, 65] |
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- | 1.1403 | 3.0 | 6 | 1.0984 | 0.29 | 0.2690 | 0.3126 | 0.3101 | [29, 71, 129, 71] |
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- | 1.036 | 4.0 | 8 | 1.0990 | 0.33 | 0.3230 | 0.4078 | 0.3634 | [33, 67, 133, 67] |
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- | 1.0479 | 5.0 | 10 | 1.1012 | 0.29 | 0.2323 | 0.2227 | 0.3219 | [29, 71, 129, 71] |
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- | 1.0699 | 6.0 | 12 | 1.1005 | 0.32 | 0.2765 | 0.2791 | 0.3371 | [32, 68, 132, 68] |
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- | 1.0234 | 7.0 | 14 | 1.1034 | 0.33 | 0.3272 | 0.3593 | 0.3494 | [33, 67, 133, 67] |
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- | 0.972 | 8.0 | 16 | 1.1107 | 0.31 | 0.3127 | 0.3593 | 0.3270 | [31, 69, 131, 69] |
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- | 0.8933 | 9.0 | 18 | 1.1269 | 0.31 | 0.2887 | 0.3551 | 0.3335 | [31, 69, 131, 69] |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4775
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+ - Accuracy: 0.5090
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+ - F1 Macro: 0.5104
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+ - Precision Macro: 0.5256
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+ - Recall Macro: 0.5035
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+ - Total Tf: [141, 136, 418, 136]
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  ## Model description
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 44
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  - num_epochs: 25
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Total Tf |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:--------------------:|
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+ | 1.1054 | 1.0 | 45 | 1.0933 | 0.4260 | 0.3340 | 0.2854 | 0.4121 | [118, 159, 395, 159] |
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+ | 1.093 | 2.0 | 90 | 1.0883 | 0.4043 | 0.3453 | 0.4086 | 0.4022 | [112, 165, 389, 165] |
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+ | 1.0147 | 3.0 | 135 | 1.0815 | 0.4224 | 0.3938 | 0.4036 | 0.4101 | [117, 160, 394, 160] |
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+ | 0.7902 | 4.0 | 180 | 1.0939 | 0.4043 | 0.4048 | 0.4039 | 0.4194 | [112, 165, 389, 165] |
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+ | 0.6868 | 5.0 | 225 | 1.0402 | 0.5235 | 0.5231 | 0.5251 | 0.5215 | [145, 132, 422, 132] |
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+ | 0.4888 | 6.0 | 270 | 1.1546 | 0.5018 | 0.4950 | 0.5219 | 0.4883 | [139, 138, 416, 138] |
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+ | 0.3871 | 7.0 | 315 | 1.2866 | 0.4946 | 0.4871 | 0.5166 | 0.4803 | [137, 140, 414, 140] |
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+ | 0.3217 | 8.0 | 360 | 1.3147 | 0.5090 | 0.5025 | 0.5474 | 0.4943 | [141, 136, 418, 136] |
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+ | 0.2213 | 9.0 | 405 | 1.4559 | 0.4729 | 0.4765 | 0.4884 | 0.4704 | [131, 146, 408, 146] |
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+ | 0.2051 | 10.0 | 450 | 1.4775 | 0.5090 | 0.5104 | 0.5256 | 0.5035 | [141, 136, 418, 136] |
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  ### Framework versions
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