End of training

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: rlcc-appearance-upsample_replacement-absa-avg
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# rlcc-appearance-upsample_replacement-absa-avg
+
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5832
+- Accuracy: 0.6512
+- F1 Macro: 0.6175
+- Precision Macro: 0.6196
+- Recall Macro: 0.6284
+- Total Tf: [267, 143, 1087, 143]
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 65
+- num_epochs: 25
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Total Tf              |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:---------------------:|
+| 1.0983        | 1.0   | 66   | 1.0816          | 0.5707   | 0.4937   | 0.5162          | 0.5104       | [234, 176, 1054, 176] |
+| 1.0066        | 2.0   | 132  | 1.0376          | 0.6268   | 0.5145   | 0.4757          | 0.5695       | [257, 153, 1077, 153] |
+| 0.938         | 3.0   | 198  | 1.0321          | 0.6293   | 0.5938   | 0.6134          | 0.6210       | [258, 152, 1078, 152] |
+| 0.7799        | 4.0   | 264  | 1.0649          | 0.6537   | 0.6215   | 0.6371          | 0.6464       | [268, 142, 1088, 142] |
+| 0.6479        | 5.0   | 330  | 1.1215          | 0.6634   | 0.6268   | 0.6332          | 0.6363       | [272, 138, 1092, 138] |
+| 0.541         | 6.0   | 396  | 1.2126          | 0.6659   | 0.6328   | 0.6444          | 0.6322       | [273, 137, 1093, 137] |
+| 0.4776        | 7.0   | 462  | 1.2496          | 0.6537   | 0.6222   | 0.6248          | 0.6379       | [268, 142, 1088, 142] |
+| 0.375         | 8.0   | 528  | 1.3441          | 0.6585   | 0.6292   | 0.6279          | 0.6313       | [270, 140, 1090, 140] |
+| 0.3663        | 9.0   | 594  | 1.4417          | 0.6317   | 0.5984   | 0.5967          | 0.6128       | [259, 151, 1079, 151] |
+| 0.2935        | 10.0  | 660  | 1.5452          | 0.6488   | 0.6147   | 0.6149          | 0.6147       | [266, 144, 1086, 144] |
+| 0.2331        | 11.0  | 726  | 1.5832          | 0.6512   | 0.6175   | 0.6196          | 0.6284       | [267, 143, 1087, 143] |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "absa_method": "avg",
+  "architectures": [
+    "BERTModel"
+  ],
+  "class_weight": null,
+  "class_weights": null,
+  "model_type": "bert_with_absa",
+  "num_classes": 3,
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.0"
+}

model.safetensors

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+oid sha256:c0b5cbd19431a318f86097b1f9e618b547b18630ff82bc2b3c88cc115d81d940
+size 875933980

training_args.bin

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+size 5368