End of training

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: rlcc-new-appearance-upsample_replacement-absa-min-aspect_classifier
+  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-new-appearance-upsample_replacement-absa-min-aspect_classifier
+
+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: 1.0247
+- Accuracy: 0.4693
+- F1 Macro: 0.4695
+- Precision Macro: 0.4729
+- Recall Macro: 0.4826
+- F1 Micro: 0.4693
+- Precision Micro: 0.4693
+- Recall Micro: 0.4693
+- Total Tf: [130, 147, 407, 147]
+
+## 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 OptimizerNames.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: 44
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | F1 Micro | Precision Micro | Recall Micro | Total Tf             |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------------------:|
+| 1.0981        | 1.0   | 45   | 1.0861          | 0.3935   | 0.3356   | 0.4043          | 0.3942       | 0.3935   | 0.3935          | 0.3935       | [109, 168, 386, 168] |
+| 1.0748        | 2.0   | 90   | 1.0651          | 0.3971   | 0.3807   | 0.3876          | 0.3972       | 0.3971   | 0.3971          | 0.3971       | [110, 167, 387, 167] |
+| 0.9543        | 3.0   | 135  | 1.0440          | 0.4513   | 0.4503   | 0.4654          | 0.4645       | 0.4513   | 0.4513          | 0.4513       | [125, 152, 402, 152] |
+| 0.8502        | 4.0   | 180  | 1.0247          | 0.4693   | 0.4695   | 0.4729          | 0.4826       | 0.4693   | 0.4693          | 0.4693       | [130, 147, 407, 147] |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.2

config.json

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+{
+  "absa_method": "min",
+  "architectures": [
+    "BERTModelNoAs"
+  ],
+  "class_weight": null,
+  "model_type": "bert_with_absa_no_as_cl",
+  "num_classes": 3,
+  "torch_dtype": "float32",
+  "transformers_version": "4.52.4"
+}

model.safetensors

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+size 437961724

training_args.bin

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+size 5368