End of training

README.md

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+---
+library_name: transformers
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: rlcc-palate-upsample_replacement-absa-None
+  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-palate-upsample_replacement-absa-None
+
+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: 1.8831
+- Accuracy: 0.8049
+- F1 Macro: 0.5751
+- Precision Macro: 0.5829
+- Recall Macro: 0.6074
+- Total Tf: [330, 80, 1150, 80]
+
+## 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: 36
+- num_epochs: 25
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Total Tf            |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------------:|:------------:|:-------------------:|
+| 1.1239        | 1.0   | 37   | 1.0929          | 0.7854   | 0.4581   | 0.4644          | 0.4843       | [322, 88, 1142, 88] |
+| 1.0966        | 2.0   | 74   | 1.0095          | 0.8049   | 0.4341   | 0.4847          | 0.4513       | [330, 80, 1150, 80] |
+| 0.9736        | 3.0   | 111  | 1.0467          | 0.8098   | 0.5311   | 0.5396          | 0.5271       | [332, 78, 1152, 78] |
+| 0.7549        | 4.0   | 148  | 1.0651          | 0.7976   | 0.5381   | 0.5417          | 0.5606       | [327, 83, 1147, 83] |
+| 0.6054        | 5.0   | 185  | 1.1613          | 0.8122   | 0.5799   | 0.5767          | 0.6065       | [333, 77, 1153, 77] |
+| 0.4563        | 6.0   | 222  | 1.3234          | 0.8146   | 0.5998   | 0.6069          | 0.6501       | [334, 76, 1154, 76] |
+| 0.3093        | 7.0   | 259  | 1.3972          | 0.8146   | 0.5904   | 0.5941          | 0.6094       | [334, 76, 1154, 76] |
+| 0.1836        | 8.0   | 296  | 1.7261          | 0.8049   | 0.5787   | 0.5880          | 0.6291       | [330, 80, 1150, 80] |
+| 0.1617        | 9.0   | 333  | 1.7743          | 0.8049   | 0.5791   | 0.5951          | 0.6291       | [330, 80, 1150, 80] |
+| 0.1209        | 10.0  | 370  | 1.9516          | 0.8073   | 0.5921   | 0.6081          | 0.6603       | [331, 79, 1151, 79] |
+| 0.0736        | 11.0  | 407  | 1.8831          | 0.8049   | 0.5751   | 0.5829          | 0.6074       | [330, 80, 1150, 80] |
+
+
+### 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": null,
+  "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:e74bef5cb991e99062428bbbb836e54b9dc3db35ec6574c920e514296c76ff13
+size 437963716

training_args.bin

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+size 5368